Train 1D CNN

1D Convolution을 기본 구성 요소로 하는 EEG classifier를 학습해보는 노트북.

• Three-way SoftMax classifier of normal, non-vascular MCI, and non-vascular dementia

---

환경 구성

# for auto-reloading external modules
# see http://stackoverflow.com/questions/1907993/autoreload-of-modules-in-ipython
%load_ext autoreload
%autoreload 2

# Load some packages
import os
import glob
import json
from copy import deepcopy
import datetime

import matplotlib.pyplot as plt
import pprint
from IPython.display import clear_output
from tqdm.auto import tqdm

import numpy as np
import random
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.utils.data import DataLoader
from torchvision import transforms
from typing import Type, Any, Callable, Union, List, Optional

# custom package
from utils.eeg_dataset import *

# Other settings
%matplotlib inline
%config InlineBackend.figure_format = 'retina' # cleaner text

plt.style.use('default') 
# ['Solarize_Light2', '_classic_test_patch', 'bmh', 'classic', 'dark_background', 'fast', 
#  'fivethirtyeight', 'ggplot', 'grayscale', 'seaborn', 'seaborn-bright', 'seaborn-colorblind', 
#  'seaborn-dark', 'seaborn-dark-palette', 'seaborn-darkgrid', 'seaborn-deep', 'seaborn-muted', 
#  'seaborn-notebook', 'seaborn-paper', 'seaborn-pastel', 'seaborn-poster', 'seaborn-talk', 
#  'seaborn-ticks', 'seaborn-white', 'seaborn-whitegrid', 'tableau-colorblind10']

plt.rcParams['image.interpolation'] = 'nearest'
plt.rcParams["font.family"] = 'NanumGothic' # for Hangul in Windows

print('PyTorch version:', torch.__version__)
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')

if torch.cuda.is_available(): print('cuda is available.')
else: print('cuda is unavailable.')

PyTorch version: 1.7.1
cuda is available.

# Data file path
root_path = r'dataset/02_Curated_Data/'

# Checkpoint
save_checkpoint = True

meta_path = os.path.join(root_path, 'metadata_debug.json')
with open(meta_path, 'r') as json_file:
    metadata = json.load(json_file)

pprint.pprint(metadata[0])

{'age': 78,
 'birth': '1940-06-02',
 'dx1': 'mci_rf',
 'edfname': '00001809_261018',
 'events': [[0, 'Start Recording'],
            [0, 'New Montage - Montage 002'],
            [36396, 'Eyes Open'],
            [72518, 'Eyes Closed'],
            [73862, 'Eyes Open'],
            [75248, 'Eyes Closed'],
            [76728, 'swallowing'],
            [77978, 'Eyes Open'],
            [79406, 'Eyes Closed'],
            [79996, 'Photic On - 3.0 Hz'],
            [80288, 'Eyes Open'],
            [81296, 'Eyes Closed'],
            [82054, 'Photic Off'],
            [84070, 'Photic On - 6.0 Hz'],
            [84488, 'Eyes Open'],
            [85538, 'Eyes Closed'],
            [86086, 'Photic Off'],
            [88144, 'Photic On - 9.0 Hz'],
            [90160, 'Photic Off'],
            [91458, 'Eyes Open'],
            [92218, 'Photic On - 12.0 Hz'],
            [92762, 'Eyes Closed'],
            [94198, 'Photic Off'],
            [94742, 'Eyes Open'],
            [95708, 'Eyes Closed'],
            [96256, 'Photic On - 15.0 Hz'],
            [98272, 'Photic Off'],
            [100330, 'Photic On - 18.0 Hz'],
            [102346, 'Photic Off'],
            [102596, 'Eyes Open'],
            [103856, 'Eyes Closed'],
            [104361, 'Photic On - 21.0 Hz'],
            [106420, 'Photic Off'],
            [106880, 'Eyes Open'],
            [107804, 'Eyes Closed'],
            [108435, 'Photic On - 24.0 Hz'],
            [110452, 'Photic Off'],
            [111080, 'Eyes Open'],
            [112004, 'Eyes Closed'],
            [112509, 'Photic On - 27.0 Hz'],
            [114528, 'Photic Off'],
            [114864, 'Eyes Open'],
            [116124, 'Eyes Closed'],
            [116544, 'Photic On - 30.0 Hz'],
            [118602, 'Photic Off'],
            [126672, 'artifact'],
            [134030, 'Move'],
            [135584, 'Eyes Open'],
            [136668, 'Eyes Closed'],
            [139818, 'Eyes Open'],
            [141414, 'Eyes Closed'],
            [145000, 'Paused']],
 'label': ['mci', 'mci_amnestic', 'mci_amnestic_rf'],
 'record': '2018-10-26T15:46:26',
 'serial': '00001'}

---

Data Filtering by Diagnosis

Non-Vascular Dementia, Non-Vascular MCI, Normal

diagnosis_filter = [
    # Normal
    {'type': 'Normal',
     'include': ['normal'], 
     'exclude': []},
    # Non-vascular MCI
    {'type': 'MCI or Dementia',
     'include': ['mci', 'dementia'], 
     'exclude': []},
]

def generate_class_label(label):
    for c, f in enumerate(diagnosis_filter):
        # inc = set(f['include']) & set(label) == set(f['include'])
        inc = len(set(f['include']) & set(label)) > 0        
        exc = len(set(f['exclude']) & set(label)) == 0
        if  inc and exc:
            return (c, f['type'])
    return (-1, 'The others')

class_label_to_type = [d_f['type'] for d_f in diagnosis_filter]
print('class_label_to_type:', class_label_to_type)

class_label_to_type: ['Normal', 'MCI or Dementia']

splitted_metadata = [[] for i in diagnosis_filter]

for m in metadata:
    c, n = generate_class_label(m['label'])
    if c >= 0:
        m['class_type'] = n
        m['class_label'] = c
        splitted_metadata[c].append(m)
        
for i, split in enumerate(splitted_metadata):
    if len(split) == 0:
        print(f'(Warning) Split group {i} has no data.')
    else:
        print(f'- There are {len(split):} data belonging to {split[0]["class_type"]}')

- There are 463 data belonging to Normal
- There are 724 data belonging to MCI or Dementia

---

Configure the Train, Validation, and Test Splits

Split the filtered dataset and shuffle them

# random seed
random.seed(0)

# Train : Val : Test = 8 : 1 : 1
ratio1 = 0.8
ratio2 = 0.1

metadata_train = []
metadata_val = []
metadata_test = []

for split in splitted_metadata:
    random.shuffle(split)
    
    n1 = round(len(split) * ratio1)
    n2 = n1 + round(len(split) * ratio2)

    metadata_train.extend(split[:n1])
    metadata_val.extend(split[n1:n2])
    metadata_test.extend(split[n2:])

random.shuffle(metadata_train)
random.shuffle(metadata_val)
random.shuffle(metadata_test)

print('Train data size\t\t:', len(metadata_train))
print('Validation data size\t:', len(metadata_val))
print('Test data size\t\t:', len(metadata_test))

print('\n', '--- Recheck ---', '\n')
train_class_nums = np.zeros((len(class_label_to_type)), dtype=np.int32)
for m in metadata_train:
    train_class_nums[m['class_label']] += 1

val_class_nums = np.zeros((len(class_label_to_type)), dtype=np.int32)
for m in metadata_val:
    val_class_nums[m['class_label']] += 1

test_class_nums = np.zeros((len(class_label_to_type)), dtype=np.int32)
for m in metadata_test:
    test_class_nums[m['class_label']] += 1

print('Train data label distribution\t:', train_class_nums, train_class_nums.sum())
print('Val data label distribution\t:', val_class_nums, val_class_nums.sum())
print('Test data label distribution\t:', test_class_nums, test_class_nums.sum())

# random seed
random.seed()

# print([m['serial']  for m in metadata_train[:15]])
# print([m['serial']  for m in metadata_val[:15]])
# print([m['serial']  for m in metadata_test[:15]])

Train data size		: 949
Validation data size	: 118
Test data size		: 120

 --- Recheck --- 

Train data label distribution	: [370 579] 949
Val data label distribution	: [46 72] 118
Test data label distribution	: [47 73] 120

Wrap the splitted data using PyTorch Dataset

ages = []
for m in metadata_train:
    ages.append(m['age'])

ages = np.array(ages)
age_mean = np.mean(ages)
age_std = np.std(ages)

print('Age mean and standard deviation:')
print(age_mean, age_std)

Age mean and standard deviation:
71.20758693361434 9.797857089966335

composed = transforms.Compose([EEGNormalizeAge(mean=age_mean, std=age_std),
                               EEGDropPhoticChannel(),
                               EEGRandomCrop(crop_length=200*10), # 10 sec
                               EEGNormalizePerSignal(),
                               EEGToTensor()])

train_dataset = EEGDataset(root_path, metadata_train, composed)
val_dataset = EEGDataset(root_path, metadata_val, composed)
test_dataset = EEGDataset(root_path, metadata_test, composed)

print(train_dataset[0]['signal'].shape)
print(train_dataset[0])

print()
print('-' * 100)
print()

print(val_dataset[0]['signal'].shape)
print(val_dataset[0])

print()
print('-' * 100)
print()

print(test_dataset[0]['signal'].shape)
print(test_dataset[0])

torch.Size([20, 2000])
{'signal': tensor([[-0.2622, -0.4226, -0.5028,  ..., -1.6255, -1.5453, -1.4651],
        [-1.2972, -1.4482, -1.4482,  ..., -1.4482, -1.4482, -1.1462],
        [ 0.0336, -0.2786, -0.9030,  ..., -0.7469, -1.0591, -1.0591],
        ...,
        [-0.0555, -0.7934, -1.9001,  ..., -0.2400, -0.0555,  0.1289],
        [ 0.3004, -0.0905, -0.8724,  ...,  1.2778,  1.8642,  1.8642],
        [ 0.5496,  0.4864,  0.3996,  ..., -0.1612, -0.1928, -0.2007]]), 'age': tensor(0.1829), 'class_label': tensor(1), 'metadata': {'serial': '01315', 'edfname': '01379199_220618', 'birth': '1945-01-07', 'record': '2018-06-22T08:55:30', 'age': 73, 'dx1': 'load', 'label': ['dementia', 'ad', 'load'], 'events': [[0, 'Start Recording'], [0, 'New Montage - Montage 002'], [15941, 'artifact'], [36936, 'Eyes Open'], [37744, 'artifact'], [70640, 'Eyes Closed'], [72388, 'Eyes Open'], [73608, 'Eyes Closed'], [76388, 'Eyes Open'], [78566, 'Eyes Closed'], [80202, 'Photic On - 3.0 Hz'], [80544, 'Eyes Open'], [81164, 'Eyes Closed'], [81806, 'artifact'], [82218, 'Photic Off'], [84280, 'Photic On - 6.0 Hz'], [86296, 'Photic Off'], [86580, 'Eyes Open'], [87810, 'Eyes Closed'], [88102, 'artifact'], [88314, 'Photic On - 9.0 Hz'], [90330, 'Photic Off'], [92388, 'Photic On - 12.0 Hz'], [94404, 'Photic Off'], [94788, 'artifact'], [95832, 'Awake'], [96462, 'Photic On - 15.0 Hz'], [98478, 'Photic Off'], [100500, 'Photic On - 18.0 Hz'], [102516, 'Photic Off'], [104574, 'Photic On - 21.0 Hz'], [106590, 'Photic Off'], [106883, 'Eyes Open'], [107976, 'Eyes Closed'], [108606, 'Photic On - 24.0 Hz'], [110664, 'Photic Off'], [112680, 'Photic On - 27.0 Hz'], [114696, 'Photic Off'], [116754, 'Photic On - 30.0 Hz'], [118770, 'Photic Off'], [118932, 'artifact'], [120409, 'Eyes Open'], [121524, 'artifact'], [122594, 'Eyes Closed'], [126800, 'Paused']], 'class_type': 'MCI or Dementia', 'class_label': 1}}

----------------------------------------------------------------------------------------------------

torch.Size([20, 2000])
{'signal': tensor([[-0.1877, -0.1957, -0.2010,  ..., -1.8883, -1.8989, -1.9176],
        [ 0.9318,  1.0977,  1.0977,  ..., -0.8931, -0.8378, -0.8378],
        [ 0.9605,  1.1771,  1.6101,  ...,  0.0944,  0.7440,  0.9605],
        ...,
        [ 0.2970,  0.5910,  0.8850,  ...,  1.9141,  2.3551,  2.7961],
        [ 0.2231,  0.3580,  0.3580,  ...,  2.2472,  2.7869,  3.0568],
        [ 0.4906,  0.3999,  0.3394,  ...,  1.2771,  1.1863,  1.1258]]), 'age': tensor(-2.2666), 'class_label': tensor(0), 'metadata': {'serial': '00754', 'edfname': '01035046_020715', 'birth': '1965-09-15', 'record': '2015-07-02T13:20:15', 'age': 49, 'dx1': 'cb_normal', 'label': ['normal', 'cb_normal'], 'events': [[0, 'Start Recording'], [0, 'New Montage - Montage 002'], [462, 'Eyes Open'], [6090, 'Eyes Closed'], [12348, 'Eyes Open'], [19320, 'Eyes Closed'], [24822, 'Eyes Open'], [30239, 'Eyes Closed'], [36330, 'Eyes Open'], [42294, 'Eyes Closed'], [53340, 'Eyes Open'], [54138, 'Eyes Closed'], [62286, 'Eyes Open'], [66234, 'Eyes Closed'], [72240, 'Eyes Open'], [79800, 'Eyes Closed'], [85260, 'Eyes Open'], [93996, 'Eyes Closed'], [102102, 'Eyes Closed'], [107730, 'Eyes Open'], [113861, 'Eyes Closed'], [120600, 'Paused']], 'class_type': 'Normal', 'class_label': 0}}

----------------------------------------------------------------------------------------------------

torch.Size([20, 2000])
{'signal': tensor([[ 0.0062, -0.0128, -0.0191,  ...,  0.9455,  0.9455,  0.9328],
        [-0.0837, -0.0837, -0.1406,  ..., -0.2543, -0.1406, -0.1975],
        [-0.3594, -0.3594, -0.2465,  ..., -0.2465, -0.2465, -0.3594],
        ...,
        [ 1.2682,  1.4674,  1.6665,  ..., -0.9226, -1.1218, -1.1218],
        [ 0.1531,  0.3737,  0.5943,  ...,  0.1531,  0.1531, -0.0675],
        [-0.1850, -0.2098, -0.1353,  ...,  0.8709,  0.5480,  0.3616]]), 'age': tensor(1.6118), 'class_label': tensor(1), 'metadata': {'serial': '01183', 'edfname': '01303198_020317', 'birth': '1929-10-31', 'record': '2017-03-02T14:10:12', 'age': 87, 'dx1': 'mci retrieval failure', 'label': ['mci', 'mci_amnestic', 'mci_amnestic_rf'], 'events': [[0, 'Start Recording'], [0, 'New Montage - Montage 002'], [1444, 'Eyes Open'], [6106, 'Eyes Closed'], [12196, 'Eyes Open'], [17994, 'Eyes Closed'], [24126, 'Eyes Open'], [30177, 'Eyes Closed'], [36226, 'Eyes Open'], [42022, 'Eyes Closed'], [48952, 'Eyes Open'], [54790, 'Eyes Closed'], [60166, 'Eyes Open'], [66256, 'Eyes Closed'], [73774, 'Eyes Open'], [78016, 'Eyes Closed'], [84192, 'Eyes Open'], [90198, 'Eyes Closed'], [95754, 'Move'], [96372, 'Eyes Open'], [101798, 'A2 Recheck'], [101800, 'Paused'], [110200, 'Recording Resumed'], [112416, 'Eyes Closed'], [116448, 'Eyes Open'], [122332, 'Eyes Closed'], [130359, 'Eyes Open'], [131746, 'Eyes Closed'], [132796, 'Photic On - 3.0 Hz'], [133510, 'Eyes Open'], [134224, 'Eyes Closed'], [134812, 'Photic Off'], [136870, 'Photic On - 6.0 Hz'], [137416, 'Eyes Open'], [138298, 'Eyes Closed'], [138886, 'Photic Off'], [140944, 'Photic On - 9.0 Hz'], [141574, 'Eyes Open'], [142330, 'Eyes Closed'], [142960, 'Photic Off'], [144976, 'Photic On - 12.0 Hz'], [145564, 'Eyes Open'], [146320, 'Eyes Closed'], [146992, 'Photic Off'], [149050, 'Photic On - 15.0 Hz'], [151066, 'Photic Off'], [153124, 'Photic On - 18.0 Hz'], [153712, 'Eyes Open'], [154510, 'Eyes Closed'], [155140, 'Photic Off'], [157156, 'Photic On - 21.0 Hz'], [159172, 'Photic Off'], [161230, 'Photic On - 24.0 Hz'], [163246, 'Photic Off'], [163540, 'Eyes Open'], [164464, 'Eyes Closed'], [165304, 'Photic On - 27.0 Hz'], [167320, 'Photic Off'], [169336, 'Photic On - 30.0 Hz'], [171352, 'Photic Off'], [171772, 'Eyes Open'], [173452, 'Eyes Closed'], [181474, 'Eyes Open'], [183196, 'Eyes Closed'], [185200, 'Paused']], 'class_type': 'MCI or Dementia', 'class_label': 1}}

Data loader test

print('Current PyTorch device:', device)
if device.type == 'cuda':
    num_workers = 0 # A number other than 0 causes an error
    pin_memory = True
else:
    num_workers = 0
    pin_memory = False

train_loader = DataLoader(train_dataset, 
                          batch_size=32, 
                          shuffle=True, 
                          drop_last=True,
                          num_workers=num_workers, 
                          pin_memory=pin_memory,
                          collate_fn=eeg_collate_fn)

for i_batch, sample_batched in enumerate(train_loader):
    sample_batched['signal'].to(device)
    sample_batched['age'].to(device)
    sample_batched['class_label'].to(device)
    
    print(i_batch, 
          sample_batched['signal'].shape, 
          sample_batched['age'].shape, 
          sample_batched['class_label'].shape, 
          len(sample_batched['metadata']))
    
    if i_batch > 3:
        break

Current PyTorch device: cuda
0 torch.Size([32, 20, 2000]) torch.Size([32]) torch.Size([32]) 32
1 torch.Size([32, 20, 2000]) torch.Size([32]) torch.Size([32]) 32
2 torch.Size([32, 20, 2000]) torch.Size([32]) torch.Size([32]) 32
3 torch.Size([32, 20, 2000]) torch.Size([32]) torch.Size([32]) 32
4 torch.Size([32, 20, 2000]) torch.Size([32]) torch.Size([32]) 32

Train, validation, test dataloaders

train_loader = DataLoader(train_dataset, 
                          batch_size=32, 
                          shuffle=True, 
                          drop_last=True,
                          num_workers=num_workers, 
                          pin_memory=pin_memory,
                          collate_fn=eeg_collate_fn)

val_loader = DataLoader(val_dataset, 
                        batch_size=32, 
                        shuffle=False, 
                        drop_last=False,
                        num_workers=num_workers, 
                        pin_memory=pin_memory,
                        collate_fn=eeg_collate_fn)

test_loader = DataLoader(test_dataset, 
                         batch_size=32, 
                         shuffle=False, 
                         drop_last=False,
                         num_workers=num_workers, 
                         pin_memory=pin_memory,
                         collate_fn=eeg_collate_fn)

---

Some useful functions for training

from torch.utils.tensorboard import SummaryWriter
import ipynbname
nb_fname = ipynbname.name()


def count_parameters(model):
    return sum(p.numel() for p in model.parameters() if p.requires_grad)


def visualize_network_tensorboard(model, name):
    # default `log_dir` is "runs" - we'll be more specific here
    writer = SummaryWriter('runs/' + nb_fname + '_' + name)

    for batch_i, sample_batched in enumerate(train_loader):
        # pull up the batch data
        x = sample_batched['signal'].to(device)
        age = sample_batched['age'].to(device)
        target = sample_batched['class_label'].to(device)

        # apply model on whole batch directly on device
        writer.add_graph(model, (x, age))
        output = model(x, age, print_shape=True)
        break
        
    writer.close()

def train_one_epoch(model, optimizer, log_interval):
    # turn the models to training mode
    model.train()
    losses = []
    correct, total = (0, 0)
    
    C = len(class_label_to_type)
    train_confusion = np.zeros((C, C), dtype=np.int32)
    
    for batch_i, sample_batched in enumerate(train_loader):
        # pull up the batch data
        x = sample_batched['signal'].to(device)
        age = sample_batched['age'].to(device)
        target = sample_batched['class_label'].to(device)
        
        # apply model on whole batch directly on device
        output = model(x, age)

        # negative log-likelihood for a tensor of size (batch x n_output)
        pred = F.log_softmax(output, dim=1)
        loss = F.nll_loss(pred, target)
        
        # backprop and update
        loss.backward()
        optimizer.step()
        optimizer.zero_grad()
        
        # record loss
        losses.append(loss.item())

        # train accuracy
        pred = pred.argmax(dim=-1)
        correct += pred.squeeze().eq(target).sum().item()
        total += pred.shape[0]
        
        # confusion matrix
        train_confusion += calculate_confusion_matrix(pred, target)

        # print training stats
        if log_interval is not None and (batch_i + 1) % log_interval == 0:
            print(f'- Iter {batch_i + 1:03d} / {len(train_loader):03d}, Loss: {loss.item():.06f}')
    
    train_accuracy = 100.0 * correct / total
    return (losses, train_accuracy, train_confusion)


def check_val_accuracy(model, repeat=1):
    model.eval()
    correct, total = (0, 0)
        
    C = len(class_label_to_type)
    val_confusion = np.zeros((C, C), dtype=np.int32)
    
    for k in range(repeat):
        for sample_batched in val_loader:
            # pull up the data
            x = sample_batched['signal'].to(device)
            age = sample_batched['age'].to(device)
            target = sample_batched['class_label'].to(device)

            # apply model on whole batch directly on device
            output = model(x, age)
            pred = F.log_softmax(output, dim=1)

            # val accuracy
            pred = pred.argmax(dim=-1)
            correct += pred.squeeze().eq(target).sum().item()
            total += pred.shape[0]
            
            # confusion matrix
            val_confusion += calculate_confusion_matrix(pred, target)
            
    val_accuracy = 100.0 * correct / total
    return (val_accuracy, val_confusion)

    
def check_test_accuracy(model, repeat=1):
    model.eval()
    correct, total = (0, 0)
    
    C = len(class_label_to_type)
    test_confusion = np.zeros((C, C), dtype=np.int32)
    
    test_debug = {data['metadata']['serial']: 
                  {'GT': data['class_label'].item(), 
                   'Acc': 0, 
                   'Pred': [0] * C} for data in test_dataset}
        
    for k in range(repeat):
        for sample_batched in test_loader:
            # pull up the data
            x = sample_batched['signal'].to(device)
            age = sample_batched['age'].to(device)
            target = sample_batched['class_label'].to(device)

            # apply model on whole batch directly on device
            output = model(x, age)
            pred = F.log_softmax(output, dim=1)
            
            # test accuracy
            pred = pred.argmax(dim=-1)
            correct += pred.squeeze().eq(target).sum().item()
            total += pred.shape[0]
            
            # confusion matrix
            test_confusion += calculate_confusion_matrix(pred, target)
            
            # test debug
            for n in range(pred.shape[0]):
                serial = sample_batched['metadata'][n]['serial']
                test_debug[serial]['edfname'] = sample_batched['metadata'][n]['edfname']
                test_debug[serial]['Pred'][pred[n].item()] += 1
                acc = test_debug[serial]['Pred'][target[n].item()] / np.sum(test_debug[serial]['Pred']) * 100
                test_debug[serial]['Acc'] = f'{acc:>6.02f}%'
        
    test_accuracy = 100.0 * correct / total
    return (test_accuracy, test_confusion, test_debug)


def calculate_confusion_matrix(pred, target):
    N = target.shape[0]
    C = len(class_label_to_type)
    confusion = np.zeros((C, C), dtype=np.int32)
    
    for i in range(N):
        r = target[i]
        c = pred[i]
        confusion[r, c] += 1
    return confusion

def draw_loss_plot(loss_history):
    plt.style.use('default') # default, ggplot, fivethirtyeight, classic
    
    fig = plt.figure(num=1, clear=True, figsize=(15.0, 6.0), constrained_layout=True)
    ax = fig.add_subplot(1, 1, 1)
    ax.plot(loss_history)
    
    ax.vlines(0, 0, 1, transform=ax.get_xaxis_transform(), colors='k', alpha=0.1)    
    for e in range(1, n_epoch + 1):
        
        if e % lr_schedule_step == 0:
            ax.vlines(e*len(train_loader) - 1, 0, 1, transform=ax.get_xaxis_transform(), colors='m', alpha=0.3)
        else:
            ax.vlines(e*len(train_loader) - 1, 0, 1, transform=ax.get_xaxis_transform(), colors='k', alpha=0.1)
    
    ax.set_title('Loss Plot')
    ax.set_xlabel('Iteration')
    ax.set_ylabel('Training Loss')
    
    plt.show()
    fig.clear()
    plt.close(fig)


def draw_accuracy_history(train_acc_history, val_acc_history):
    plt.style.use('default') # default, ggplot, fivethirtyeight, classic
    
    fig = plt.figure(num=1, clear=True, figsize=(15.0, 6.0), constrained_layout=True)
    ax = fig.add_subplot(1, 1, 1)
    ax.plot(train_acc_history, 'r-', label='Train accuracy')
    ax.plot(val_acc_history, 'b-', label='Validation accuracy')
    ax.legend(loc='lower right')
    
    ax.set_title('Accuracy Plot during Training')
    ax.set_xlabel('Epoch')
    ax.set_ylabel('Accuracy (%)')
    
    plt.show()
    fig.clear()
    plt.close(fig)


def draw_confusion(confusion):
    C = len(class_label_to_type)
    
    plt.style.use('default') # default, ggplot, fivethirtyeight, classic
    plt.rcParams['image.cmap'] = 'jet' # 'nipy_spectral'

    fig = plt.figure(num=1, clear=True, figsize=(5.0, 5.0), constrained_layout=True)
    ax = fig.add_subplot(1, 1, 1)
    im = ax.imshow(confusion, alpha=0.8)

    ax.set_xticks(np.arange(C))
    ax.set_yticks(np.arange(C))
    ax.set_xticklabels(class_label_to_type)
    ax.set_yticklabels(class_label_to_type)
    
    for r in range(C):
        for c in range(C):
            text = ax.text(c, r, confusion[r, c],
                           ha="center", va="center", color='k')
    
    ax.set_title('Confusion Matrix')
    ax.set_xlabel('Prediction')
    ax.set_ylabel('Ground Truth')
    plt.setp(ax.get_xticklabels(), rotation=45, ha="right", rotation_mode="anchor")
    
    plt.show()
    fig.clear()
    plt.close(fig)

def learning_rate_search(model, min_log_lr, max_log_lr, trials, epochs):
    learning_rate_record = []
    for t in tqdm(range(trials)):
        log_lr = np.random.uniform(min_log_lr, max_log_lr)
        lr = 10 ** log_lr
        
        model.reset_weights()
        optimizer = optim.AdamW(model.parameters(), lr=lr, weight_decay=0.0001)

        for e in range(epochs):
            _, train_accuracy, _ = train_one_epoch(model, optimizer, log_interval=None)
        
        # Train accuracy for the final epoch is stored
        learning_rate_record.append((log_lr, train_accuracy))
    
    return learning_rate_record


def draw_learning_rate_record(learning_rate_record):
    plt.style.use('default') # default, ggplot, fivethirtyeight, classic

    fig = plt.figure(num=1, clear=True, figsize=(8.0, 8.0), constrained_layout=True)
    ax = fig.add_subplot(1, 1, 1)
    
    ax.set_title('Learning Rate Search')
    ax.set_xlabel('Learning rate in log-scale')
    ax.set_ylabel('Train accuracy')
    
    for log_lr, val_accuracy in learning_rate_record:
        ax.scatter(log_lr, val_accuracy, c='r',
                   alpha=0.5, edgecolors='none')
    
    plt.show()
    fig.clear()
    plt.close(fig)

---

Train 1D CNN models

1D CNN: Tiny model

class TinyNet(nn.Module):
    def __init__(self, n_input=20, n_output=3, stride=7, n_channel=64, 
                 use_age=True, final_pool='average'):
        super().__init__()
        
        if final_pool not in {'average', 'max'}:
            raise ValueError("final_pool must be set to one of ['average', 'max']")
        
        self.use_age = use_age
        
        self.conv1 = nn.Conv1d(n_input, n_channel, kernel_size=35, stride=stride)
        self.bn1 = nn.BatchNorm1d(n_channel)
        self.pool1 = nn.MaxPool1d(4)
        
        self.conv2 = nn.Conv1d(n_channel, n_channel, kernel_size=7)
        self.bn2 = nn.BatchNorm1d(n_channel)
        self.pool2 = nn.MaxPool1d(2)
        
        if final_pool == 'average':
            self.final_pool = nn.AdaptiveAvgPool1d(1)
        elif final_pool == 'max':
            self.final_pool = nn.AdaptiveMaxPool1d(1)
        
        if self.use_age:        
            self.fc1 = nn.Linear(n_channel + 1, n_channel)
        else:
            self.fc1 = nn.Linear(n_channel, n_channel)
            
        self.dropout = nn.Dropout(p=0.3)
        self.bnfc1 = nn.BatchNorm1d(n_channel)
        self.fc2 = nn.Linear(n_channel, n_output)
        
    def reset_weights(self):
        for m in self.modules():
            if hasattr(m, 'reset_parameters'):
                m.reset_parameters()

    def forward(self, x, age, print_shape=False):
        # conv-bn-relu-pool 
        x = self.conv1(x)
        x = F.relu(self.bn1(x))
        x = self.pool1(x)

        x = self.conv2(x)
        x = F.relu(self.bn2(x))
        x = self.pool2(x)

        if print_shape:
            print('Shape right before squeezing:', x.shape)

        x = self.final_pool(x).squeeze()
        if self.use_age:
            x = torch.cat((x, age.reshape(-1, 1)), dim=1)

        # fc-bn-dropout-relu-fc
        x = self.fc1(x)
        x = self.bnfc1(x)
        x = self.dropout(x)
        x = F.relu(x)
        x = self.fc2(x)
        
        return x
        # return F.log_softmax(x, dim=1)

model = TinyNet(n_input=train_dataset[0]['signal'].shape[0], 
                n_output=2, 
                use_age=True, 
                final_pool='max')

model = model.to(device, dtype=torch.float32)
print(model)
print()

# tensorboard visualization
visualize_network_tensorboard(model, 'TinyNet')

# number of parameters
n = count_parameters(model)
print(f'The Number of parameters of the model: {n:,}')

TinyNet(
  (conv1): Conv1d(20, 64, kernel_size=(35,), stride=(7,))
  (bn1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (pool1): MaxPool1d(kernel_size=4, stride=4, padding=0, dilation=1, ceil_mode=False)
  (conv2): Conv1d(64, 64, kernel_size=(7,), stride=(1,))
  (bn2): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (pool2): MaxPool1d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
  (final_pool): AdaptiveMaxPool1d(output_size=1)
  (fc1): Linear(in_features=65, out_features=64, bias=True)
  (dropout): Dropout(p=0.3, inplace=False)
  (bnfc1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (fc2): Linear(in_features=64, out_features=2, bias=True)
)

Shape right before squeezing: torch.Size([32, 64, 32])
The Number of parameters of the model: 78,338

record = learning_rate_search(model, 
                              min_log_lr=-4.5, 
                              max_log_lr=-1.4, 
                              trials=300, 
                              epochs=1)
draw_learning_rate_record(record)
best_log_lr = record[np.argmax(np.array([v for lr, v in record]))][0]

# best_log_lr = -1.9358023684588126
print('best_log_lr:', best_log_lr)

best_log_lr: -2.019390017755719

# reduce the learning after [lr_schedule_step] epochs by a factor of 10
n_epoch = 500
lr_schedule_step = 200
log_interval = len(train_loader) // 2

loss_history = []
train_acc_history = []
val_acc_history = []
best_val_acc = 0

model.reset_weights()
optimizer = optim.AdamW(model.parameters(), lr=10 ** best_log_lr, weight_decay=0.0001)
scheduler = optim.lr_scheduler.StepLR(optimizer, step_size=lr_schedule_step, gamma=0.1)

print(f'{"*"*40} Training Starts {"*"*40}')

for epoch in tqdm(range(1, n_epoch + 1)):
    print(f'{"-"*30} Epoch {epoch:03d} / {n_epoch:03d}, Learning rate: {optimizer.param_groups[-1]["lr"]:.2e} {"-"*30}')
    
    # train
    loss, train_accuracy, train_confusion = train_one_epoch(model, optimizer, log_interval)
    loss_history.extend(loss)
    train_acc_history.append(train_accuracy)
    
    # validation
    val_accuracy, val_confusion = check_val_accuracy(model, repeat=5)
    val_acc_history.append(val_accuracy)
    
    if best_val_acc < val_accuracy:
        best_val_acc = val_accuracy
        best_model_state = deepcopy(model.state_dict())
    
    # learning rate schedule
    scheduler.step()
    
    print()
    print(f'* Train accuracy / confusion: {train_accuracy:.2f}% / {train_confusion.tolist()}, ')
    print(f'* Val   accuracy / confusion: {val_accuracy:.2f}% / {val_confusion.tolist()}')
    print()

print(f'{"*"*40} Training Ends {"*"*40}')

# draw the training loss plot
draw_loss_plot(loss_history)
draw_accuracy_history(train_acc_history, val_acc_history)
    
# test the last model
last_model_state = deepcopy(model.state_dict())
last_test_accuracy, last_test_confusion, last_test_debug = check_test_accuracy(model, repeat=30)

print(f'- Test accuracy (last model): {last_test_accuracy:.2f}%')
print('- Confusion matrix (last model):\n', last_test_confusion)
print()

draw_confusion(last_test_confusion)

# test the best model
model.load_state_dict(best_model_state)
best_test_accuracy, best_test_confusion, best_test_debug = check_test_accuracy(model, repeat=30)

print(f'- Test accuracy (best model): {best_test_accuracy:.2f}%')
print('- Confusion matrix (best model):\n', best_test_confusion)
print()

draw_confusion(best_test_confusion)

**************************************** Training Starts ****************************************

------------------------------ Epoch 001 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.668572
- Iter 028 / 029, Loss: 0.881718

* Train accuracy / confusion: 64.98% / [[168, 194], [131, 435]], 
* Val   accuracy / confusion: 68.81% / [[147, 83], [101, 259]]

------------------------------ Epoch 002 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.526744
- Iter 028 / 029, Loss: 0.617468

* Train accuracy / confusion: 69.18% / [[184, 175], [111, 458]], 
* Val   accuracy / confusion: 74.41% / [[113, 117], [34, 326]]

------------------------------ Epoch 003 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.472982
- Iter 028 / 029, Loss: 0.610683

* Train accuracy / confusion: 71.01% / [[190, 171], [98, 469]], 
* Val   accuracy / confusion: 68.98% / [[50, 180], [3, 357]]

------------------------------ Epoch 004 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.671066
- Iter 028 / 029, Loss: 0.583764

* Train accuracy / confusion: 73.81% / [[226, 139], [104, 459]], 
* Val   accuracy / confusion: 74.07% / [[132, 98], [55, 305]]

------------------------------ Epoch 005 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.633374
- Iter 028 / 029, Loss: 0.557135

* Train accuracy / confusion: 74.25% / [[221, 138], [101, 468]], 
* Val   accuracy / confusion: 72.37% / [[149, 81], [82, 278]]

------------------------------ Epoch 006 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.507040
- Iter 028 / 029, Loss: 0.597523

* Train accuracy / confusion: 75.11% / [[220, 141], [90, 477]], 
* Val   accuracy / confusion: 70.34% / [[183, 47], [128, 232]]

------------------------------ Epoch 007 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.618383
- Iter 028 / 029, Loss: 0.423324

* Train accuracy / confusion: 70.58% / [[207, 155], [118, 448]], 
* Val   accuracy / confusion: 73.56% / [[103, 127], [29, 331]]

------------------------------ Epoch 008 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.710068
- Iter 028 / 029, Loss: 0.474291

* Train accuracy / confusion: 72.95% / [[201, 158], [93, 476]], 
* Val   accuracy / confusion: 73.56% / [[137, 93], [63, 297]]

------------------------------ Epoch 009 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.409016
- Iter 028 / 029, Loss: 0.430339

* Train accuracy / confusion: 75.86% / [[229, 133], [91, 475]], 
* Val   accuracy / confusion: 74.41% / [[140, 90], [61, 299]]

------------------------------ Epoch 010 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.426734
- Iter 028 / 029, Loss: 0.585581

* Train accuracy / confusion: 73.28% / [[218, 146], [102, 462]], 
* Val   accuracy / confusion: 73.05% / [[121, 109], [50, 310]]

------------------------------ Epoch 011 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.446481
- Iter 028 / 029, Loss: 0.492804

* Train accuracy / confusion: 73.28% / [[214, 145], [103, 466]], 
* Val   accuracy / confusion: 74.07% / [[155, 75], [78, 282]]

------------------------------ Epoch 012 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.574971
- Iter 028 / 029, Loss: 0.449792

* Train accuracy / confusion: 71.44% / [[188, 171], [94, 475]], 
* Val   accuracy / confusion: 73.05% / [[100, 130], [29, 331]]

------------------------------ Epoch 013 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.468102
- Iter 028 / 029, Loss: 0.406084

* Train accuracy / confusion: 73.71% / [[229, 135], [109, 455]], 
* Val   accuracy / confusion: 74.24% / [[145, 85], [67, 293]]

------------------------------ Epoch 014 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.436877
- Iter 028 / 029, Loss: 0.476081

* Train accuracy / confusion: 72.74% / [[190, 169], [84, 485]], 
* Val   accuracy / confusion: 74.07% / [[137, 93], [60, 300]]

------------------------------ Epoch 015 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.520898
- Iter 028 / 029, Loss: 0.506459

* Train accuracy / confusion: 74.35% / [[214, 147], [91, 476]], 
* Val   accuracy / confusion: 70.51% / [[83, 147], [27, 333]]

------------------------------ Epoch 016 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.761953
- Iter 028 / 029, Loss: 0.583534

* Train accuracy / confusion: 72.41% / [[206, 157], [99, 466]], 
* Val   accuracy / confusion: 73.73% / [[151, 79], [76, 284]]

------------------------------ Epoch 017 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.528065
- Iter 028 / 029, Loss: 0.370549

* Train accuracy / confusion: 74.03% / [[216, 148], [93, 471]], 
* Val   accuracy / confusion: 72.54% / [[123, 107], [55, 305]]

------------------------------ Epoch 018 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.391812
- Iter 028 / 029, Loss: 0.388295

* Train accuracy / confusion: 75.11% / [[226, 134], [97, 471]], 
* Val   accuracy / confusion: 70.51% / [[77, 153], [21, 339]]

------------------------------ Epoch 019 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.502255
- Iter 028 / 029, Loss: 0.549699

* Train accuracy / confusion: 76.19% / [[210, 152], [69, 497]], 
* Val   accuracy / confusion: 72.54% / [[137, 93], [69, 291]]

------------------------------ Epoch 020 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.467958
- Iter 028 / 029, Loss: 0.681855

* Train accuracy / confusion: 75.54% / [[219, 139], [88, 482]], 
* Val   accuracy / confusion: 70.68% / [[112, 118], [55, 305]]

------------------------------ Epoch 021 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.531876
- Iter 028 / 029, Loss: 0.572209

* Train accuracy / confusion: 75.11% / [[200, 160], [71, 497]], 
* Val   accuracy / confusion: 73.05% / [[97, 133], [26, 334]]

------------------------------ Epoch 022 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.604309
- Iter 028 / 029, Loss: 0.479502

* Train accuracy / confusion: 75.97% / [[236, 125], [98, 469]], 
* Val   accuracy / confusion: 70.68% / [[123, 107], [66, 294]]

------------------------------ Epoch 023 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.574145
- Iter 028 / 029, Loss: 0.438158

* Train accuracy / confusion: 75.65% / [[236, 126], [100, 466]], 
* Val   accuracy / confusion: 73.73% / [[147, 83], [72, 288]]

------------------------------ Epoch 024 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.537515
- Iter 028 / 029, Loss: 0.551224

* Train accuracy / confusion: 75.43% / [[212, 149], [79, 488]], 
* Val   accuracy / confusion: 72.88% / [[138, 92], [68, 292]]

------------------------------ Epoch 025 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.551787
- Iter 028 / 029, Loss: 0.404473

* Train accuracy / confusion: 77.59% / [[236, 129], [79, 484]], 
* Val   accuracy / confusion: 72.37% / [[147, 83], [80, 280]]

------------------------------ Epoch 026 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.520127
- Iter 028 / 029, Loss: 0.543123

* Train accuracy / confusion: 75.54% / [[221, 139], [88, 480]], 
* Val   accuracy / confusion: 73.56% / [[123, 107], [49, 311]]

------------------------------ Epoch 027 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.466712
- Iter 028 / 029, Loss: 0.385948

* Train accuracy / confusion: 76.08% / [[222, 141], [81, 484]], 
* Val   accuracy / confusion: 74.75% / [[154, 76], [73, 287]]

------------------------------ Epoch 028 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.573395
- Iter 028 / 029, Loss: 0.586678

* Train accuracy / confusion: 75.97% / [[229, 134], [89, 476]], 
* Val   accuracy / confusion: 73.56% / [[101, 129], [27, 333]]

------------------------------ Epoch 029 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.362962
- Iter 028 / 029, Loss: 0.469283

* Train accuracy / confusion: 74.78% / [[222, 139], [95, 472]], 
* Val   accuracy / confusion: 73.56% / [[114, 116], [40, 320]]

------------------------------ Epoch 030 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.620964
- Iter 028 / 029, Loss: 0.425586

* Train accuracy / confusion: 76.40% / [[211, 154], [65, 498]], 
* Val   accuracy / confusion: 73.56% / [[155, 75], [81, 279]]

------------------------------ Epoch 031 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.472351
- Iter 028 / 029, Loss: 0.417186

* Train accuracy / confusion: 76.83% / [[226, 133], [82, 487]], 
* Val   accuracy / confusion: 74.58% / [[147, 83], [67, 293]]

------------------------------ Epoch 032 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.530236
- Iter 028 / 029, Loss: 0.403145

* Train accuracy / confusion: 78.02% / [[243, 122], [82, 481]], 
* Val   accuracy / confusion: 74.41% / [[140, 90], [61, 299]]

------------------------------ Epoch 033 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.438339
- Iter 028 / 029, Loss: 0.515647

* Train accuracy / confusion: 76.19% / [[232, 131], [90, 475]], 
* Val   accuracy / confusion: 71.53% / [[125, 105], [63, 297]]

------------------------------ Epoch 034 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.613742
- Iter 028 / 029, Loss: 0.460383

* Train accuracy / confusion: 75.11% / [[222, 142], [89, 475]], 
* Val   accuracy / confusion: 72.03% / [[125, 105], [60, 300]]

------------------------------ Epoch 035 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.468278
- Iter 028 / 029, Loss: 0.754086

* Train accuracy / confusion: 76.72% / [[235, 127], [89, 477]], 
* Val   accuracy / confusion: 73.73% / [[148, 82], [73, 287]]

------------------------------ Epoch 036 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.688809
- Iter 028 / 029, Loss: 0.455067

* Train accuracy / confusion: 75.00% / [[212, 151], [81, 484]], 
* Val   accuracy / confusion: 75.08% / [[119, 111], [36, 324]]

------------------------------ Epoch 037 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.520838
- Iter 028 / 029, Loss: 0.511904

* Train accuracy / confusion: 77.16% / [[227, 131], [81, 489]], 
* Val   accuracy / confusion: 75.08% / [[146, 84], [63, 297]]

------------------------------ Epoch 038 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.439832
- Iter 028 / 029, Loss: 0.635341

* Train accuracy / confusion: 75.11% / [[212, 154], [77, 485]], 
* Val   accuracy / confusion: 74.24% / [[159, 71], [81, 279]]

------------------------------ Epoch 039 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.450567
- Iter 028 / 029, Loss: 0.418565

* Train accuracy / confusion: 76.19% / [[218, 142], [79, 489]], 
* Val   accuracy / confusion: 73.05% / [[116, 114], [45, 315]]

------------------------------ Epoch 040 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.678954
- Iter 028 / 029, Loss: 0.619836

* Train accuracy / confusion: 77.59% / [[228, 131], [77, 492]], 
* Val   accuracy / confusion: 72.88% / [[135, 95], [65, 295]]

------------------------------ Epoch 041 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.376858
- Iter 028 / 029, Loss: 0.429223

* Train accuracy / confusion: 77.26% / [[238, 125], [86, 479]], 
* Val   accuracy / confusion: 73.56% / [[153, 77], [79, 281]]

------------------------------ Epoch 042 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.503489
- Iter 028 / 029, Loss: 0.343160

* Train accuracy / confusion: 76.62% / [[238, 124], [93, 473]], 
* Val   accuracy / confusion: 74.92% / [[128, 102], [46, 314]]

------------------------------ Epoch 043 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.496059
- Iter 028 / 029, Loss: 0.515448

* Train accuracy / confusion: 78.02% / [[227, 132], [72, 497]], 
* Val   accuracy / confusion: 73.39% / [[147, 83], [74, 286]]

------------------------------ Epoch 044 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.873340
- Iter 028 / 029, Loss: 0.574297

* Train accuracy / confusion: 75.11% / [[220, 142], [89, 477]], 
* Val   accuracy / confusion: 73.39% / [[119, 111], [46, 314]]

------------------------------ Epoch 045 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.425212
- Iter 028 / 029, Loss: 0.383417

* Train accuracy / confusion: 76.08% / [[230, 134], [88, 476]], 
* Val   accuracy / confusion: 73.05% / [[103, 127], [32, 328]]

------------------------------ Epoch 046 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.455808
- Iter 028 / 029, Loss: 0.543164

* Train accuracy / confusion: 76.40% / [[219, 143], [76, 490]], 
* Val   accuracy / confusion: 72.20% / [[141, 89], [75, 285]]

------------------------------ Epoch 047 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.451983
- Iter 028 / 029, Loss: 0.387870

* Train accuracy / confusion: 77.69% / [[245, 121], [86, 476]], 
* Val   accuracy / confusion: 75.25% / [[124, 106], [40, 320]]

------------------------------ Epoch 048 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.545023
- Iter 028 / 029, Loss: 0.441992

* Train accuracy / confusion: 76.51% / [[223, 140], [78, 487]], 
* Val   accuracy / confusion: 72.20% / [[135, 95], [69, 291]]

------------------------------ Epoch 049 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.561956
- Iter 028 / 029, Loss: 0.421531

* Train accuracy / confusion: 77.16% / [[234, 128], [84, 482]], 
* Val   accuracy / confusion: 72.37% / [[132, 98], [65, 295]]

------------------------------ Epoch 050 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.473038
- Iter 028 / 029, Loss: 0.605678

* Train accuracy / confusion: 77.37% / [[239, 123], [87, 479]], 
* Val   accuracy / confusion: 74.24% / [[107, 123], [29, 331]]

------------------------------ Epoch 051 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.501304
- Iter 028 / 029, Loss: 0.473580

* Train accuracy / confusion: 77.26% / [[215, 142], [69, 502]], 
* Val   accuracy / confusion: 72.88% / [[141, 89], [71, 289]]

------------------------------ Epoch 052 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.369645
- Iter 028 / 029, Loss: 0.609837

* Train accuracy / confusion: 77.26% / [[228, 132], [79, 489]], 
* Val   accuracy / confusion: 72.71% / [[137, 93], [68, 292]]

------------------------------ Epoch 053 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.335017
- Iter 028 / 029, Loss: 0.375401

* Train accuracy / confusion: 75.43% / [[216, 147], [81, 484]], 
* Val   accuracy / confusion: 74.58% / [[140, 90], [60, 300]]

------------------------------ Epoch 054 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.667297
- Iter 028 / 029, Loss: 0.447985

* Train accuracy / confusion: 78.34% / [[231, 128], [73, 496]], 
* Val   accuracy / confusion: 72.88% / [[125, 105], [55, 305]]

------------------------------ Epoch 055 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.416542
- Iter 028 / 029, Loss: 0.563778

* Train accuracy / confusion: 77.37% / [[232, 131], [79, 486]], 
* Val   accuracy / confusion: 74.41% / [[134, 96], [55, 305]]

------------------------------ Epoch 056 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.507353
- Iter 028 / 029, Loss: 0.494910

* Train accuracy / confusion: 76.83% / [[221, 140], [75, 492]], 
* Val   accuracy / confusion: 74.24% / [[136, 94], [58, 302]]

------------------------------ Epoch 057 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.342829
- Iter 028 / 029, Loss: 0.455360

* Train accuracy / confusion: 77.37% / [[224, 137], [73, 494]], 
* Val   accuracy / confusion: 73.73% / [[115, 115], [40, 320]]

------------------------------ Epoch 058 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.447359
- Iter 028 / 029, Loss: 0.438919

* Train accuracy / confusion: 75.75% / [[220, 143], [82, 483]], 
* Val   accuracy / confusion: 76.78% / [[147, 83], [54, 306]]

------------------------------ Epoch 059 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.487179
- Iter 028 / 029, Loss: 0.399704

* Train accuracy / confusion: 78.12% / [[241, 122], [81, 484]], 
* Val   accuracy / confusion: 72.71% / [[173, 57], [104, 256]]

------------------------------ Epoch 060 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.589891
- Iter 028 / 029, Loss: 0.369608

* Train accuracy / confusion: 77.59% / [[227, 137], [71, 493]], 
* Val   accuracy / confusion: 72.88% / [[96, 134], [26, 334]]

------------------------------ Epoch 061 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.557061
- Iter 028 / 029, Loss: 0.612388

* Train accuracy / confusion: 78.88% / [[237, 121], [75, 495]], 
* Val   accuracy / confusion: 73.05% / [[138, 92], [67, 293]]

------------------------------ Epoch 062 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.432142
- Iter 028 / 029, Loss: 0.571337

* Train accuracy / confusion: 76.83% / [[225, 134], [81, 488]], 
* Val   accuracy / confusion: 71.53% / [[173, 57], [111, 249]]

------------------------------ Epoch 063 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.597579
- Iter 028 / 029, Loss: 0.752412

* Train accuracy / confusion: 78.99% / [[237, 127], [68, 496]], 
* Val   accuracy / confusion: 73.39% / [[131, 99], [58, 302]]

------------------------------ Epoch 064 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.531925
- Iter 028 / 029, Loss: 0.414573

* Train accuracy / confusion: 79.20% / [[248, 115], [78, 487]], 
* Val   accuracy / confusion: 72.20% / [[138, 92], [72, 288]]

------------------------------ Epoch 065 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.639599
- Iter 028 / 029, Loss: 0.423873

* Train accuracy / confusion: 78.12% / [[233, 127], [76, 492]], 
* Val   accuracy / confusion: 73.56% / [[141, 89], [67, 293]]

------------------------------ Epoch 066 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.509683
- Iter 028 / 029, Loss: 0.520998

* Train accuracy / confusion: 76.40% / [[216, 144], [75, 493]], 
* Val   accuracy / confusion: 75.59% / [[134, 96], [48, 312]]

------------------------------ Epoch 067 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.487896
- Iter 028 / 029, Loss: 0.576633

* Train accuracy / confusion: 76.51% / [[231, 133], [85, 479]], 
* Val   accuracy / confusion: 70.68% / [[95, 135], [38, 322]]

------------------------------ Epoch 068 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.539319
- Iter 028 / 029, Loss: 0.493818

* Train accuracy / confusion: 78.77% / [[246, 115], [82, 485]], 
* Val   accuracy / confusion: 72.88% / [[129, 101], [59, 301]]

------------------------------ Epoch 069 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.525087
- Iter 028 / 029, Loss: 0.493206

* Train accuracy / confusion: 77.26% / [[226, 135], [76, 491]], 
* Val   accuracy / confusion: 73.56% / [[161, 69], [87, 273]]

------------------------------ Epoch 070 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.456662
- Iter 028 / 029, Loss: 0.503828

* Train accuracy / confusion: 76.19% / [[216, 145], [76, 491]], 
* Val   accuracy / confusion: 75.59% / [[126, 104], [40, 320]]

------------------------------ Epoch 071 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.484894
- Iter 028 / 029, Loss: 0.522164

* Train accuracy / confusion: 77.37% / [[242, 120], [90, 476]], 
* Val   accuracy / confusion: 73.05% / [[144, 86], [73, 287]]

------------------------------ Epoch 072 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.392491
- Iter 028 / 029, Loss: 0.372010

* Train accuracy / confusion: 79.09% / [[237, 122], [72, 497]], 
* Val   accuracy / confusion: 74.07% / [[131, 99], [54, 306]]

------------------------------ Epoch 073 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.475420
- Iter 028 / 029, Loss: 0.713606

* Train accuracy / confusion: 78.45% / [[245, 116], [84, 483]], 
* Val   accuracy / confusion: 73.39% / [[109, 121], [36, 324]]

------------------------------ Epoch 074 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.465055
- Iter 028 / 029, Loss: 0.613222

* Train accuracy / confusion: 76.19% / [[210, 152], [69, 497]], 
* Val   accuracy / confusion: 72.88% / [[137, 93], [67, 293]]

------------------------------ Epoch 075 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.426370
- Iter 028 / 029, Loss: 0.379520

* Train accuracy / confusion: 76.72% / [[233, 133], [83, 479]], 
* Val   accuracy / confusion: 73.39% / [[157, 73], [84, 276]]

------------------------------ Epoch 076 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.452641
- Iter 028 / 029, Loss: 0.350981

* Train accuracy / confusion: 79.09% / [[245, 117], [77, 489]], 
* Val   accuracy / confusion: 74.24% / [[125, 105], [47, 313]]

------------------------------ Epoch 077 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.464150
- Iter 028 / 029, Loss: 0.633700

* Train accuracy / confusion: 76.94% / [[234, 129], [85, 480]], 
* Val   accuracy / confusion: 71.19% / [[142, 88], [82, 278]]

------------------------------ Epoch 078 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.393666
- Iter 028 / 029, Loss: 0.527371

* Train accuracy / confusion: 77.48% / [[231, 131], [78, 488]], 
* Val   accuracy / confusion: 71.69% / [[138, 92], [75, 285]]

------------------------------ Epoch 079 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.357352
- Iter 028 / 029, Loss: 0.437051

* Train accuracy / confusion: 77.91% / [[239, 121], [84, 484]], 
* Val   accuracy / confusion: 74.07% / [[127, 103], [50, 310]]

------------------------------ Epoch 080 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.515849
- Iter 028 / 029, Loss: 0.414050

* Train accuracy / confusion: 78.56% / [[237, 130], [69, 492]], 
* Val   accuracy / confusion: 74.58% / [[157, 73], [77, 283]]

------------------------------ Epoch 081 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.498219
- Iter 028 / 029, Loss: 0.528496

* Train accuracy / confusion: 78.56% / [[249, 115], [84, 480]], 
* Val   accuracy / confusion: 73.56% / [[124, 106], [50, 310]]

------------------------------ Epoch 082 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.498235
- Iter 028 / 029, Loss: 0.548501

* Train accuracy / confusion: 77.37% / [[234, 126], [84, 484]], 
* Val   accuracy / confusion: 75.42% / [[169, 61], [84, 276]]

------------------------------ Epoch 083 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.541856
- Iter 028 / 029, Loss: 0.502968

* Train accuracy / confusion: 79.42% / [[244, 116], [75, 493]], 
* Val   accuracy / confusion: 72.71% / [[117, 113], [48, 312]]

------------------------------ Epoch 084 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.263830
- Iter 028 / 029, Loss: 0.479784

* Train accuracy / confusion: 76.19% / [[228, 132], [89, 479]], 
* Val   accuracy / confusion: 72.54% / [[136, 94], [68, 292]]

------------------------------ Epoch 085 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.386693
- Iter 028 / 029, Loss: 0.496347

* Train accuracy / confusion: 76.19% / [[221, 140], [81, 486]], 
* Val   accuracy / confusion: 72.88% / [[121, 109], [51, 309]]

------------------------------ Epoch 086 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.407095
- Iter 028 / 029, Loss: 0.519997

* Train accuracy / confusion: 78.34% / [[236, 127], [74, 491]], 
* Val   accuracy / confusion: 75.59% / [[133, 97], [47, 313]]

------------------------------ Epoch 087 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.408336
- Iter 028 / 029, Loss: 0.529187

* Train accuracy / confusion: 78.12% / [[247, 115], [88, 478]], 
* Val   accuracy / confusion: 74.07% / [[143, 87], [66, 294]]

------------------------------ Epoch 088 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.410092
- Iter 028 / 029, Loss: 0.361518

* Train accuracy / confusion: 78.77% / [[243, 117], [80, 488]], 
* Val   accuracy / confusion: 71.86% / [[128, 102], [64, 296]]

------------------------------ Epoch 089 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.451775
- Iter 028 / 029, Loss: 0.328745

* Train accuracy / confusion: 77.69% / [[230, 130], [77, 491]], 
* Val   accuracy / confusion: 72.03% / [[122, 108], [57, 303]]

------------------------------ Epoch 090 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.539925
- Iter 028 / 029, Loss: 0.449726

* Train accuracy / confusion: 78.12% / [[246, 119], [84, 479]], 
* Val   accuracy / confusion: 74.07% / [[145, 85], [68, 292]]

------------------------------ Epoch 091 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.626008
- Iter 028 / 029, Loss: 0.472265

* Train accuracy / confusion: 78.66% / [[233, 126], [72, 497]], 
* Val   accuracy / confusion: 74.24% / [[131, 99], [53, 307]]

------------------------------ Epoch 092 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.490250
- Iter 028 / 029, Loss: 0.380773

* Train accuracy / confusion: 77.05% / [[235, 128], [85, 480]], 
* Val   accuracy / confusion: 73.90% / [[127, 103], [51, 309]]

------------------------------ Epoch 093 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.519861
- Iter 028 / 029, Loss: 0.399489

* Train accuracy / confusion: 79.63% / [[246, 116], [73, 493]], 
* Val   accuracy / confusion: 68.31% / [[115, 115], [72, 288]]

------------------------------ Epoch 094 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.535558
- Iter 028 / 029, Loss: 0.481188

* Train accuracy / confusion: 79.96% / [[248, 116], [70, 494]], 
* Val   accuracy / confusion: 70.34% / [[156, 74], [101, 259]]

------------------------------ Epoch 095 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.503343
- Iter 028 / 029, Loss: 0.422627

* Train accuracy / confusion: 78.99% / [[235, 126], [69, 498]], 
* Val   accuracy / confusion: 70.17% / [[173, 57], [119, 241]]

------------------------------ Epoch 096 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.553458
- Iter 028 / 029, Loss: 0.434368

* Train accuracy / confusion: 77.69% / [[243, 120], [87, 478]], 
* Val   accuracy / confusion: 74.58% / [[178, 52], [98, 262]]

------------------------------ Epoch 097 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.540780
- Iter 028 / 029, Loss: 0.384766

* Train accuracy / confusion: 76.62% / [[231, 124], [93, 480]], 
* Val   accuracy / confusion: 72.88% / [[116, 114], [46, 314]]

------------------------------ Epoch 098 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.614931
- Iter 028 / 029, Loss: 0.451019

* Train accuracy / confusion: 77.80% / [[230, 131], [75, 492]], 
* Val   accuracy / confusion: 74.58% / [[134, 96], [54, 306]]

------------------------------ Epoch 099 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.458141
- Iter 028 / 029, Loss: 0.557460

* Train accuracy / confusion: 78.45% / [[242, 121], [79, 486]], 
* Val   accuracy / confusion: 75.42% / [[146, 84], [61, 299]]

------------------------------ Epoch 100 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.515131
- Iter 028 / 029, Loss: 0.410509

* Train accuracy / confusion: 79.20% / [[239, 123], [70, 496]], 
* Val   accuracy / confusion: 75.25% / [[146, 84], [62, 298]]

------------------------------ Epoch 101 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.658817
- Iter 028 / 029, Loss: 0.430686

* Train accuracy / confusion: 78.99% / [[237, 122], [73, 496]], 
* Val   accuracy / confusion: 75.59% / [[144, 86], [58, 302]]

------------------------------ Epoch 102 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.358905
- Iter 028 / 029, Loss: 0.380119

* Train accuracy / confusion: 76.94% / [[225, 137], [77, 489]], 
* Val   accuracy / confusion: 72.88% / [[101, 129], [31, 329]]

------------------------------ Epoch 103 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.563392
- Iter 028 / 029, Loss: 0.375598

* Train accuracy / confusion: 76.62% / [[232, 130], [87, 479]], 
* Val   accuracy / confusion: 75.59% / [[148, 82], [62, 298]]

------------------------------ Epoch 104 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.463252
- Iter 028 / 029, Loss: 0.490775

* Train accuracy / confusion: 77.91% / [[236, 125], [80, 487]], 
* Val   accuracy / confusion: 74.41% / [[145, 85], [66, 294]]

------------------------------ Epoch 105 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.407403
- Iter 028 / 029, Loss: 0.483304

* Train accuracy / confusion: 78.66% / [[244, 120], [78, 486]], 
* Val   accuracy / confusion: 72.54% / [[141, 89], [73, 287]]

------------------------------ Epoch 106 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.425269
- Iter 028 / 029, Loss: 0.465290

* Train accuracy / confusion: 78.34% / [[242, 122], [79, 485]], 
* Val   accuracy / confusion: 75.25% / [[142, 88], [58, 302]]

------------------------------ Epoch 107 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.363668
- Iter 028 / 029, Loss: 0.359940

* Train accuracy / confusion: 78.12% / [[232, 129], [74, 493]], 
* Val   accuracy / confusion: 74.58% / [[162, 68], [82, 278]]

------------------------------ Epoch 108 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.412587
- Iter 028 / 029, Loss: 0.350866

* Train accuracy / confusion: 80.50% / [[248, 113], [68, 499]], 
* Val   accuracy / confusion: 74.24% / [[144, 86], [66, 294]]

------------------------------ Epoch 109 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.448561
- Iter 028 / 029, Loss: 0.481127

* Train accuracy / confusion: 77.91% / [[235, 125], [80, 488]], 
* Val   accuracy / confusion: 74.07% / [[131, 99], [54, 306]]

------------------------------ Epoch 110 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.713030
- Iter 028 / 029, Loss: 0.427297

* Train accuracy / confusion: 78.12% / [[224, 135], [68, 501]], 
* Val   accuracy / confusion: 72.20% / [[149, 81], [83, 277]]

------------------------------ Epoch 111 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.533735
- Iter 028 / 029, Loss: 0.456320

* Train accuracy / confusion: 79.63% / [[248, 113], [76, 491]], 
* Val   accuracy / confusion: 75.59% / [[155, 75], [69, 291]]

------------------------------ Epoch 112 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.568775
- Iter 028 / 029, Loss: 0.420789

* Train accuracy / confusion: 77.37% / [[230, 130], [80, 488]], 
* Val   accuracy / confusion: 72.54% / [[104, 126], [36, 324]]

------------------------------ Epoch 113 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.306609
- Iter 028 / 029, Loss: 0.484168

* Train accuracy / confusion: 79.74% / [[247, 113], [75, 493]], 
* Val   accuracy / confusion: 73.73% / [[109, 121], [34, 326]]

------------------------------ Epoch 114 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.339476
- Iter 028 / 029, Loss: 0.375661

* Train accuracy / confusion: 78.56% / [[241, 120], [79, 488]], 
* Val   accuracy / confusion: 72.88% / [[168, 62], [98, 262]]

------------------------------ Epoch 115 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.353813
- Iter 028 / 029, Loss: 0.566926

* Train accuracy / confusion: 78.34% / [[247, 114], [87, 480]], 
* Val   accuracy / confusion: 74.24% / [[139, 91], [61, 299]]

------------------------------ Epoch 116 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.463101
- Iter 028 / 029, Loss: 0.436131

* Train accuracy / confusion: 78.34% / [[234, 127], [74, 493]], 
* Val   accuracy / confusion: 75.25% / [[153, 77], [69, 291]]

------------------------------ Epoch 117 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.444261
- Iter 028 / 029, Loss: 0.363365

* Train accuracy / confusion: 78.56% / [[232, 130], [69, 497]], 
* Val   accuracy / confusion: 74.07% / [[118, 112], [41, 319]]

------------------------------ Epoch 118 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.719660
- Iter 028 / 029, Loss: 0.340411

* Train accuracy / confusion: 78.66% / [[245, 116], [82, 485]], 
* Val   accuracy / confusion: 75.93% / [[143, 87], [55, 305]]

------------------------------ Epoch 119 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.516290
- Iter 028 / 029, Loss: 0.432859

* Train accuracy / confusion: 80.06% / [[265, 96], [89, 478]], 
* Val   accuracy / confusion: 72.37% / [[104, 126], [37, 323]]

------------------------------ Epoch 120 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.330930
- Iter 028 / 029, Loss: 0.382130

* Train accuracy / confusion: 77.05% / [[223, 140], [73, 492]], 
* Val   accuracy / confusion: 71.19% / [[176, 54], [116, 244]]

------------------------------ Epoch 121 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.397200
- Iter 028 / 029, Loss: 0.410711

* Train accuracy / confusion: 79.96% / [[245, 114], [72, 497]], 
* Val   accuracy / confusion: 74.41% / [[140, 90], [61, 299]]

------------------------------ Epoch 122 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.569450
- Iter 028 / 029, Loss: 0.420696

* Train accuracy / confusion: 79.53% / [[256, 108], [82, 482]], 
* Val   accuracy / confusion: 75.42% / [[145, 85], [60, 300]]

------------------------------ Epoch 123 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.425715
- Iter 028 / 029, Loss: 0.368285

* Train accuracy / confusion: 78.12% / [[245, 111], [92, 480]], 
* Val   accuracy / confusion: 74.58% / [[140, 90], [60, 300]]

------------------------------ Epoch 124 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.493185
- Iter 028 / 029, Loss: 0.409758

* Train accuracy / confusion: 78.45% / [[246, 116], [84, 482]], 
* Val   accuracy / confusion: 73.22% / [[151, 79], [79, 281]]

------------------------------ Epoch 125 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.445793
- Iter 028 / 029, Loss: 0.337245

* Train accuracy / confusion: 79.53% / [[249, 114], [76, 489]], 
* Val   accuracy / confusion: 71.19% / [[98, 132], [38, 322]]

------------------------------ Epoch 126 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.345856
- Iter 028 / 029, Loss: 0.275453

* Train accuracy / confusion: 81.03% / [[253, 106], [70, 499]], 
* Val   accuracy / confusion: 73.05% / [[134, 96], [63, 297]]

------------------------------ Epoch 127 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.554959
- Iter 028 / 029, Loss: 0.493006

* Train accuracy / confusion: 79.09% / [[245, 117], [77, 489]], 
* Val   accuracy / confusion: 72.88% / [[116, 114], [46, 314]]

------------------------------ Epoch 128 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.494626
- Iter 028 / 029, Loss: 0.386622

* Train accuracy / confusion: 78.66% / [[245, 115], [83, 485]], 
* Val   accuracy / confusion: 71.36% / [[140, 90], [79, 281]]

------------------------------ Epoch 129 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.326060
- Iter 028 / 029, Loss: 0.586922

* Train accuracy / confusion: 79.09% / [[236, 125], [69, 498]], 
* Val   accuracy / confusion: 71.19% / [[91, 139], [31, 329]]

------------------------------ Epoch 130 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.478656
- Iter 028 / 029, Loss: 0.398380

* Train accuracy / confusion: 78.99% / [[242, 119], [76, 491]], 
* Val   accuracy / confusion: 72.37% / [[141, 89], [74, 286]]

------------------------------ Epoch 131 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.538438
- Iter 028 / 029, Loss: 0.486351

* Train accuracy / confusion: 78.02% / [[246, 115], [89, 478]], 
* Val   accuracy / confusion: 71.36% / [[111, 119], [50, 310]]

------------------------------ Epoch 132 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.419615
- Iter 028 / 029, Loss: 0.341354

* Train accuracy / confusion: 79.42% / [[246, 116], [75, 491]], 
* Val   accuracy / confusion: 72.20% / [[121, 109], [55, 305]]

------------------------------ Epoch 133 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.407200
- Iter 028 / 029, Loss: 0.361882

* Train accuracy / confusion: 79.74% / [[252, 115], [73, 488]], 
* Val   accuracy / confusion: 74.24% / [[171, 59], [93, 267]]

------------------------------ Epoch 134 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.489830
- Iter 028 / 029, Loss: 0.377496

* Train accuracy / confusion: 81.03% / [[258, 104], [72, 494]], 
* Val   accuracy / confusion: 73.90% / [[135, 95], [59, 301]]

------------------------------ Epoch 135 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.570949
- Iter 028 / 029, Loss: 0.658696

* Train accuracy / confusion: 78.99% / [[246, 116], [79, 487]], 
* Val   accuracy / confusion: 75.59% / [[154, 76], [68, 292]]

------------------------------ Epoch 136 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.354847
- Iter 028 / 029, Loss: 0.664944

* Train accuracy / confusion: 79.74% / [[232, 131], [57, 508]], 
* Val   accuracy / confusion: 74.41% / [[138, 92], [59, 301]]

------------------------------ Epoch 137 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.418639
- Iter 028 / 029, Loss: 0.392377

* Train accuracy / confusion: 78.02% / [[242, 121], [83, 482]], 
* Val   accuracy / confusion: 74.07% / [[112, 118], [35, 325]]

------------------------------ Epoch 138 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.465493
- Iter 028 / 029, Loss: 0.339955

* Train accuracy / confusion: 79.20% / [[247, 114], [79, 488]], 
* Val   accuracy / confusion: 69.83% / [[176, 54], [124, 236]]

------------------------------ Epoch 139 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.447959
- Iter 028 / 029, Loss: 0.535925

* Train accuracy / confusion: 79.74% / [[242, 119], [69, 498]], 
* Val   accuracy / confusion: 73.22% / [[117, 113], [45, 315]]

------------------------------ Epoch 140 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.455909
- Iter 028 / 029, Loss: 0.394782

* Train accuracy / confusion: 80.28% / [[246, 116], [67, 499]], 
* Val   accuracy / confusion: 72.88% / [[115, 115], [45, 315]]

------------------------------ Epoch 141 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.413096
- Iter 028 / 029, Loss: 0.383803

* Train accuracy / confusion: 80.28% / [[253, 108], [75, 492]], 
* Val   accuracy / confusion: 74.07% / [[130, 100], [53, 307]]

------------------------------ Epoch 142 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.434893
- Iter 028 / 029, Loss: 0.328520

* Train accuracy / confusion: 78.12% / [[242, 118], [85, 483]], 
* Val   accuracy / confusion: 71.86% / [[147, 83], [83, 277]]

------------------------------ Epoch 143 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.439000
- Iter 028 / 029, Loss: 0.544679

* Train accuracy / confusion: 80.82% / [[246, 116], [62, 504]], 
* Val   accuracy / confusion: 73.56% / [[136, 94], [62, 298]]

------------------------------ Epoch 144 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.481555
- Iter 028 / 029, Loss: 0.341664

* Train accuracy / confusion: 80.82% / [[251, 110], [68, 499]], 
* Val   accuracy / confusion: 73.39% / [[129, 101], [56, 304]]

------------------------------ Epoch 145 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.312292
- Iter 028 / 029, Loss: 0.385089

* Train accuracy / confusion: 78.12% / [[241, 119], [84, 484]], 
* Val   accuracy / confusion: 74.58% / [[134, 96], [54, 306]]

------------------------------ Epoch 146 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.469782
- Iter 028 / 029, Loss: 0.367519

* Train accuracy / confusion: 78.23% / [[232, 128], [74, 494]], 
* Val   accuracy / confusion: 76.78% / [[142, 88], [49, 311]]

------------------------------ Epoch 147 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.400958
- Iter 028 / 029, Loss: 0.535911

* Train accuracy / confusion: 80.39% / [[244, 114], [68, 502]], 
* Val   accuracy / confusion: 74.75% / [[162, 68], [81, 279]]

------------------------------ Epoch 148 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.711765
- Iter 028 / 029, Loss: 0.647820

* Train accuracy / confusion: 79.74% / [[235, 125], [63, 505]], 
* Val   accuracy / confusion: 74.24% / [[147, 83], [69, 291]]

------------------------------ Epoch 149 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.427977
- Iter 028 / 029, Loss: 0.456188

* Train accuracy / confusion: 80.82% / [[253, 106], [72, 497]], 
* Val   accuracy / confusion: 74.58% / [[148, 82], [68, 292]]

------------------------------ Epoch 150 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.271937
- Iter 028 / 029, Loss: 0.256495

* Train accuracy / confusion: 78.56% / [[236, 125], [74, 493]], 
* Val   accuracy / confusion: 73.56% / [[118, 112], [44, 316]]

------------------------------ Epoch 151 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.508135
- Iter 028 / 029, Loss: 0.689274

* Train accuracy / confusion: 79.53% / [[235, 125], [65, 503]], 
* Val   accuracy / confusion: 76.10% / [[135, 95], [46, 314]]

------------------------------ Epoch 152 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.368208
- Iter 028 / 029, Loss: 0.270714

* Train accuracy / confusion: 79.63% / [[247, 118], [71, 492]], 
* Val   accuracy / confusion: 71.53% / [[137, 93], [75, 285]]

------------------------------ Epoch 153 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.390404
- Iter 028 / 029, Loss: 0.435954

* Train accuracy / confusion: 79.74% / [[258, 107], [81, 482]], 
* Val   accuracy / confusion: 74.41% / [[141, 89], [62, 298]]

------------------------------ Epoch 154 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.646313
- Iter 028 / 029, Loss: 0.372599

* Train accuracy / confusion: 79.31% / [[239, 127], [65, 497]], 
* Val   accuracy / confusion: 74.58% / [[157, 73], [77, 283]]

------------------------------ Epoch 155 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.519071
- Iter 028 / 029, Loss: 0.447726

* Train accuracy / confusion: 81.57% / [[264, 100], [71, 493]], 
* Val   accuracy / confusion: 74.41% / [[138, 92], [59, 301]]

------------------------------ Epoch 156 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.380033
- Iter 028 / 029, Loss: 0.468195

* Train accuracy / confusion: 78.99% / [[258, 104], [91, 475]], 
* Val   accuracy / confusion: 74.92% / [[133, 97], [51, 309]]

------------------------------ Epoch 157 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.470401
- Iter 028 / 029, Loss: 0.452537

* Train accuracy / confusion: 81.03% / [[244, 116], [60, 508]], 
* Val   accuracy / confusion: 73.39% / [[127, 103], [54, 306]]

------------------------------ Epoch 158 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.651418
- Iter 028 / 029, Loss: 0.462084

* Train accuracy / confusion: 79.96% / [[248, 116], [70, 494]], 
* Val   accuracy / confusion: 73.73% / [[155, 75], [80, 280]]

------------------------------ Epoch 159 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.464037
- Iter 028 / 029, Loss: 0.447595

* Train accuracy / confusion: 80.06% / [[250, 113], [72, 493]], 
* Val   accuracy / confusion: 76.44% / [[145, 85], [54, 306]]

------------------------------ Epoch 160 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.511286
- Iter 028 / 029, Loss: 0.360596

* Train accuracy / confusion: 78.77% / [[225, 136], [61, 506]], 
* Val   accuracy / confusion: 73.05% / [[124, 106], [53, 307]]

------------------------------ Epoch 161 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.577232
- Iter 028 / 029, Loss: 0.458710

* Train accuracy / confusion: 77.91% / [[242, 118], [87, 481]], 
* Val   accuracy / confusion: 73.90% / [[138, 92], [62, 298]]

------------------------------ Epoch 162 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.476723
- Iter 028 / 029, Loss: 0.339420

* Train accuracy / confusion: 79.09% / [[235, 127], [67, 499]], 
* Val   accuracy / confusion: 73.90% / [[175, 55], [99, 261]]

------------------------------ Epoch 163 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.495040
- Iter 028 / 029, Loss: 0.431206

* Train accuracy / confusion: 80.39% / [[245, 112], [70, 501]], 
* Val   accuracy / confusion: 74.92% / [[134, 96], [52, 308]]

------------------------------ Epoch 164 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.530951
- Iter 028 / 029, Loss: 0.318379

* Train accuracy / confusion: 79.85% / [[252, 113], [74, 489]], 
* Val   accuracy / confusion: 72.54% / [[136, 94], [68, 292]]

------------------------------ Epoch 165 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.316474
- Iter 028 / 029, Loss: 0.485134

* Train accuracy / confusion: 79.53% / [[243, 114], [76, 495]], 
* Val   accuracy / confusion: 73.90% / [[133, 97], [57, 303]]

------------------------------ Epoch 166 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.528662
- Iter 028 / 029, Loss: 0.455934

* Train accuracy / confusion: 79.63% / [[249, 112], [77, 490]], 
* Val   accuracy / confusion: 72.88% / [[147, 83], [77, 283]]

------------------------------ Epoch 167 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.499491
- Iter 028 / 029, Loss: 0.475660

* Train accuracy / confusion: 80.06% / [[247, 117], [68, 496]], 
* Val   accuracy / confusion: 73.56% / [[124, 106], [50, 310]]

------------------------------ Epoch 168 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.345580
- Iter 028 / 029, Loss: 0.448700

* Train accuracy / confusion: 80.71% / [[236, 124], [55, 513]], 
* Val   accuracy / confusion: 72.71% / [[158, 72], [89, 271]]

------------------------------ Epoch 169 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.650221
- Iter 028 / 029, Loss: 0.598771

* Train accuracy / confusion: 79.20% / [[261, 102], [91, 474]], 
* Val   accuracy / confusion: 72.03% / [[104, 126], [39, 321]]

------------------------------ Epoch 170 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.344603
- Iter 028 / 029, Loss: 0.367838

* Train accuracy / confusion: 79.31% / [[233, 126], [66, 503]], 
* Val   accuracy / confusion: 73.90% / [[159, 71], [83, 277]]

------------------------------ Epoch 171 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.398215
- Iter 028 / 029, Loss: 0.435898

* Train accuracy / confusion: 79.74% / [[244, 118], [70, 496]], 
* Val   accuracy / confusion: 73.39% / [[120, 110], [47, 313]]

------------------------------ Epoch 172 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.630255
- Iter 028 / 029, Loss: 0.431778

* Train accuracy / confusion: 80.39% / [[258, 101], [81, 488]], 
* Val   accuracy / confusion: 72.88% / [[134, 96], [64, 296]]

------------------------------ Epoch 173 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.377812
- Iter 028 / 029, Loss: 0.459508

* Train accuracy / confusion: 82.44% / [[258, 100], [63, 507]], 
* Val   accuracy / confusion: 72.88% / [[144, 86], [74, 286]]

------------------------------ Epoch 174 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.401807
- Iter 028 / 029, Loss: 0.762581

* Train accuracy / confusion: 80.06% / [[245, 112], [73, 498]], 
* Val   accuracy / confusion: 74.41% / [[135, 95], [56, 304]]

------------------------------ Epoch 175 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.534364
- Iter 028 / 029, Loss: 0.487593

* Train accuracy / confusion: 78.66% / [[231, 131], [67, 499]], 
* Val   accuracy / confusion: 71.69% / [[134, 96], [71, 289]]

------------------------------ Epoch 176 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.357815
- Iter 028 / 029, Loss: 0.557465

* Train accuracy / confusion: 79.20% / [[248, 111], [82, 487]], 
* Val   accuracy / confusion: 74.41% / [[143, 87], [64, 296]]

------------------------------ Epoch 177 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.384948
- Iter 028 / 029, Loss: 0.502165

* Train accuracy / confusion: 79.74% / [[253, 113], [75, 487]], 
* Val   accuracy / confusion: 73.73% / [[139, 91], [64, 296]]

------------------------------ Epoch 178 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.446897
- Iter 028 / 029, Loss: 0.437582

* Train accuracy / confusion: 79.42% / [[246, 117], [74, 491]], 
* Val   accuracy / confusion: 71.86% / [[124, 106], [60, 300]]

------------------------------ Epoch 179 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.543410
- Iter 028 / 029, Loss: 0.465722

* Train accuracy / confusion: 77.48% / [[240, 123], [86, 479]], 
* Val   accuracy / confusion: 72.20% / [[150, 80], [84, 276]]

------------------------------ Epoch 180 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.373500
- Iter 028 / 029, Loss: 0.370872

* Train accuracy / confusion: 81.36% / [[245, 116], [57, 510]], 
* Val   accuracy / confusion: 72.71% / [[134, 96], [65, 295]]

------------------------------ Epoch 181 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.410187
- Iter 028 / 029, Loss: 0.475594

* Train accuracy / confusion: 80.06% / [[250, 105], [80, 493]], 
* Val   accuracy / confusion: 74.24% / [[138, 92], [60, 300]]

------------------------------ Epoch 182 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.548252
- Iter 028 / 029, Loss: 0.321008

* Train accuracy / confusion: 79.85% / [[243, 119], [68, 498]], 
* Val   accuracy / confusion: 72.54% / [[140, 90], [72, 288]]

------------------------------ Epoch 183 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.373194
- Iter 028 / 029, Loss: 0.494078

* Train accuracy / confusion: 79.09% / [[243, 117], [77, 491]], 
* Val   accuracy / confusion: 74.24% / [[130, 100], [52, 308]]

------------------------------ Epoch 184 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.409536
- Iter 028 / 029, Loss: 0.476097

* Train accuracy / confusion: 80.39% / [[249, 112], [70, 497]], 
* Val   accuracy / confusion: 75.08% / [[142, 88], [59, 301]]

------------------------------ Epoch 185 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.284210
- Iter 028 / 029, Loss: 0.445181

* Train accuracy / confusion: 80.82% / [[257, 106], [72, 493]], 
* Val   accuracy / confusion: 72.88% / [[103, 127], [33, 327]]

------------------------------ Epoch 186 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.280687
- Iter 028 / 029, Loss: 0.465892

* Train accuracy / confusion: 78.88% / [[246, 115], [81, 486]], 
* Val   accuracy / confusion: 74.24% / [[148, 82], [70, 290]]

------------------------------ Epoch 187 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.411422
- Iter 028 / 029, Loss: 0.422401

* Train accuracy / confusion: 80.60% / [[247, 113], [67, 501]], 
* Val   accuracy / confusion: 75.42% / [[142, 88], [57, 303]]

------------------------------ Epoch 188 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.419790
- Iter 028 / 029, Loss: 0.549909

* Train accuracy / confusion: 80.06% / [[253, 110], [75, 490]], 
* Val   accuracy / confusion: 74.07% / [[163, 67], [86, 274]]

------------------------------ Epoch 189 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.594233
- Iter 028 / 029, Loss: 0.417560

* Train accuracy / confusion: 79.63% / [[256, 107], [82, 483]], 
* Val   accuracy / confusion: 71.53% / [[154, 76], [92, 268]]

------------------------------ Epoch 190 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.395942
- Iter 028 / 029, Loss: 0.412950

* Train accuracy / confusion: 80.39% / [[248, 117], [65, 498]], 
* Val   accuracy / confusion: 72.20% / [[134, 96], [68, 292]]

------------------------------ Epoch 191 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.393183
- Iter 028 / 029, Loss: 0.394843

* Train accuracy / confusion: 79.74% / [[259, 103], [85, 481]], 
* Val   accuracy / confusion: 73.05% / [[124, 106], [53, 307]]

------------------------------ Epoch 192 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.554670
- Iter 028 / 029, Loss: 0.392585

* Train accuracy / confusion: 79.31% / [[248, 116], [76, 488]], 
* Val   accuracy / confusion: 73.22% / [[146, 84], [74, 286]]

------------------------------ Epoch 193 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.445041
- Iter 028 / 029, Loss: 0.434397

* Train accuracy / confusion: 80.93% / [[246, 116], [61, 505]], 
* Val   accuracy / confusion: 73.39% / [[144, 86], [71, 289]]

------------------------------ Epoch 194 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.344751
- Iter 028 / 029, Loss: 0.591220

* Train accuracy / confusion: 78.99% / [[255, 109], [86, 478]], 
* Val   accuracy / confusion: 77.12% / [[152, 78], [57, 303]]

------------------------------ Epoch 195 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.369714
- Iter 028 / 029, Loss: 0.266511

* Train accuracy / confusion: 81.14% / [[262, 100], [75, 491]], 
* Val   accuracy / confusion: 74.41% / [[151, 79], [72, 288]]

------------------------------ Epoch 196 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.377592
- Iter 028 / 029, Loss: 0.585019

* Train accuracy / confusion: 80.71% / [[249, 114], [65, 500]], 
* Val   accuracy / confusion: 73.05% / [[113, 117], [42, 318]]

------------------------------ Epoch 197 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.480226
- Iter 028 / 029, Loss: 0.394766

* Train accuracy / confusion: 79.74% / [[247, 115], [73, 493]], 
* Val   accuracy / confusion: 72.88% / [[124, 106], [54, 306]]

------------------------------ Epoch 198 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.509333
- Iter 028 / 029, Loss: 0.358007

* Train accuracy / confusion: 80.71% / [[249, 107], [72, 500]], 
* Val   accuracy / confusion: 74.07% / [[128, 102], [51, 309]]

------------------------------ Epoch 199 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.346694
- Iter 028 / 029, Loss: 0.469336

* Train accuracy / confusion: 79.31% / [[239, 124], [68, 497]], 
* Val   accuracy / confusion: 74.07% / [[157, 73], [80, 280]]

------------------------------ Epoch 200 / 500, Learning rate: 9.56e-03 ------------------------------
- Iter 014 / 029, Loss: 0.323045
- Iter 028 / 029, Loss: 0.412533

* Train accuracy / confusion: 79.96% / [[258, 105], [81, 484]], 
* Val   accuracy / confusion: 74.07% / [[107, 123], [30, 330]]

------------------------------ Epoch 201 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.351169
- Iter 028 / 029, Loss: 0.568605

* Train accuracy / confusion: 81.57% / [[243, 122], [49, 514]], 
* Val   accuracy / confusion: 73.39% / [[128, 102], [55, 305]]

------------------------------ Epoch 202 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.421129
- Iter 028 / 029, Loss: 0.316624

* Train accuracy / confusion: 78.99% / [[237, 124], [71, 496]], 
* Val   accuracy / confusion: 73.56% / [[133, 97], [59, 301]]

------------------------------ Epoch 203 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.632228
- Iter 028 / 029, Loss: 0.375607

* Train accuracy / confusion: 79.96% / [[242, 119], [67, 500]], 
* Val   accuracy / confusion: 74.24% / [[135, 95], [57, 303]]

------------------------------ Epoch 204 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.308610
- Iter 028 / 029, Loss: 0.697931

* Train accuracy / confusion: 79.09% / [[243, 121], [73, 491]], 
* Val   accuracy / confusion: 73.39% / [[134, 96], [61, 299]]

------------------------------ Epoch 205 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.402721
- Iter 028 / 029, Loss: 0.479184

* Train accuracy / confusion: 79.20% / [[242, 117], [76, 493]], 
* Val   accuracy / confusion: 75.08% / [[146, 84], [63, 297]]

------------------------------ Epoch 206 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.277777
- Iter 028 / 029, Loss: 0.430633

* Train accuracy / confusion: 80.50% / [[251, 108], [73, 496]], 
* Val   accuracy / confusion: 73.90% / [[136, 94], [60, 300]]

------------------------------ Epoch 207 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.270581
- Iter 028 / 029, Loss: 0.456476

* Train accuracy / confusion: 81.36% / [[261, 100], [73, 494]], 
* Val   accuracy / confusion: 73.22% / [[133, 97], [61, 299]]

------------------------------ Epoch 208 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.387242
- Iter 028 / 029, Loss: 0.480956

* Train accuracy / confusion: 81.68% / [[260, 100], [70, 498]], 
* Val   accuracy / confusion: 75.25% / [[147, 83], [63, 297]]

------------------------------ Epoch 209 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.454833
- Iter 028 / 029, Loss: 0.618584

* Train accuracy / confusion: 79.85% / [[253, 112], [75, 488]], 
* Val   accuracy / confusion: 72.54% / [[138, 92], [70, 290]]

------------------------------ Epoch 210 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.519991
- Iter 028 / 029, Loss: 0.339503

* Train accuracy / confusion: 81.68% / [[272, 94], [76, 486]], 
* Val   accuracy / confusion: 73.73% / [[144, 86], [69, 291]]

------------------------------ Epoch 211 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.357003
- Iter 028 / 029, Loss: 0.505451

* Train accuracy / confusion: 82.44% / [[265, 96], [67, 500]], 
* Val   accuracy / confusion: 72.71% / [[133, 97], [64, 296]]

------------------------------ Epoch 212 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.303015
- Iter 028 / 029, Loss: 0.457311

* Train accuracy / confusion: 82.76% / [[266, 96], [64, 502]], 
* Val   accuracy / confusion: 74.07% / [[142, 88], [65, 295]]

------------------------------ Epoch 213 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.357668
- Iter 028 / 029, Loss: 0.314535

* Train accuracy / confusion: 80.17% / [[253, 109], [75, 491]], 
* Val   accuracy / confusion: 75.25% / [[145, 85], [61, 299]]

------------------------------ Epoch 214 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.557974
- Iter 028 / 029, Loss: 0.337525

* Train accuracy / confusion: 81.79% / [[260, 105], [64, 499]], 
* Val   accuracy / confusion: 76.44% / [[145, 85], [54, 306]]

------------------------------ Epoch 215 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.469432
- Iter 028 / 029, Loss: 0.364401

* Train accuracy / confusion: 81.79% / [[263, 99], [70, 496]], 
* Val   accuracy / confusion: 75.59% / [[142, 88], [56, 304]]

------------------------------ Epoch 216 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.428869
- Iter 028 / 029, Loss: 0.434341

* Train accuracy / confusion: 79.74% / [[258, 105], [83, 482]], 
* Val   accuracy / confusion: 74.24% / [[145, 85], [67, 293]]

------------------------------ Epoch 217 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.524284
- Iter 028 / 029, Loss: 0.310029

* Train accuracy / confusion: 81.25% / [[256, 103], [71, 498]], 
* Val   accuracy / confusion: 72.03% / [[141, 89], [76, 284]]

------------------------------ Epoch 218 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.329755
- Iter 028 / 029, Loss: 0.505493

* Train accuracy / confusion: 80.60% / [[258, 107], [73, 490]], 
* Val   accuracy / confusion: 73.22% / [[133, 97], [61, 299]]

------------------------------ Epoch 219 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.410676
- Iter 028 / 029, Loss: 0.420133

* Train accuracy / confusion: 80.17% / [[245, 116], [68, 499]], 
* Val   accuracy / confusion: 70.34% / [[125, 105], [70, 290]]

------------------------------ Epoch 220 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.559369
- Iter 028 / 029, Loss: 0.407940

* Train accuracy / confusion: 80.82% / [[263, 100], [78, 487]], 
* Val   accuracy / confusion: 74.24% / [[147, 83], [69, 291]]

------------------------------ Epoch 221 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.463668
- Iter 028 / 029, Loss: 0.326558

* Train accuracy / confusion: 83.30% / [[265, 99], [56, 508]], 
* Val   accuracy / confusion: 74.24% / [[143, 87], [65, 295]]

------------------------------ Epoch 222 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.359013
- Iter 028 / 029, Loss: 0.515643

* Train accuracy / confusion: 80.60% / [[265, 100], [80, 483]], 
* Val   accuracy / confusion: 76.95% / [[155, 75], [61, 299]]

------------------------------ Epoch 223 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.265731
- Iter 028 / 029, Loss: 0.377244

* Train accuracy / confusion: 81.47% / [[265, 96], [76, 491]], 
* Val   accuracy / confusion: 74.41% / [[136, 94], [57, 303]]

------------------------------ Epoch 224 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.563402
- Iter 028 / 029, Loss: 0.383899

* Train accuracy / confusion: 80.39% / [[253, 107], [75, 493]], 
* Val   accuracy / confusion: 72.88% / [[136, 94], [66, 294]]

------------------------------ Epoch 225 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.381814
- Iter 028 / 029, Loss: 0.482833

* Train accuracy / confusion: 79.42% / [[249, 111], [80, 488]], 
* Val   accuracy / confusion: 74.92% / [[141, 89], [59, 301]]

------------------------------ Epoch 226 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.421582
- Iter 028 / 029, Loss: 0.377082

* Train accuracy / confusion: 80.71% / [[254, 108], [71, 495]], 
* Val   accuracy / confusion: 75.93% / [[145, 85], [57, 303]]

------------------------------ Epoch 227 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.476843
- Iter 028 / 029, Loss: 0.452611

* Train accuracy / confusion: 82.33% / [[257, 106], [58, 507]], 
* Val   accuracy / confusion: 74.58% / [[148, 82], [68, 292]]

------------------------------ Epoch 228 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.423557
- Iter 028 / 029, Loss: 0.496105

* Train accuracy / confusion: 80.50% / [[249, 113], [68, 498]], 
* Val   accuracy / confusion: 74.24% / [[132, 98], [54, 306]]

------------------------------ Epoch 229 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.451671
- Iter 028 / 029, Loss: 0.341423

* Train accuracy / confusion: 81.25% / [[261, 99], [75, 493]], 
* Val   accuracy / confusion: 72.88% / [[143, 87], [73, 287]]

------------------------------ Epoch 230 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.243721
- Iter 028 / 029, Loss: 0.489110

* Train accuracy / confusion: 81.57% / [[259, 103], [68, 498]], 
* Val   accuracy / confusion: 73.05% / [[141, 89], [70, 290]]

------------------------------ Epoch 231 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.618569
- Iter 028 / 029, Loss: 0.583650

* Train accuracy / confusion: 81.36% / [[256, 107], [66, 499]], 
* Val   accuracy / confusion: 72.03% / [[134, 96], [69, 291]]

------------------------------ Epoch 232 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.434861
- Iter 028 / 029, Loss: 0.282559

* Train accuracy / confusion: 80.39% / [[251, 111], [71, 495]], 
* Val   accuracy / confusion: 73.22% / [[133, 97], [61, 299]]

------------------------------ Epoch 233 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.610155
- Iter 028 / 029, Loss: 0.387109

* Train accuracy / confusion: 81.36% / [[254, 106], [67, 501]], 
* Val   accuracy / confusion: 74.24% / [[133, 97], [55, 305]]

------------------------------ Epoch 234 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.516213
- Iter 028 / 029, Loss: 0.286285

* Train accuracy / confusion: 80.60% / [[256, 108], [72, 492]], 
* Val   accuracy / confusion: 76.44% / [[135, 95], [44, 316]]

------------------------------ Epoch 235 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.323027
- Iter 028 / 029, Loss: 0.438876

* Train accuracy / confusion: 80.93% / [[246, 113], [64, 505]], 
* Val   accuracy / confusion: 73.05% / [[141, 89], [70, 290]]

------------------------------ Epoch 236 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.363482
- Iter 028 / 029, Loss: 0.375049

* Train accuracy / confusion: 82.44% / [[262, 102], [61, 503]], 
* Val   accuracy / confusion: 74.92% / [[137, 93], [55, 305]]

------------------------------ Epoch 237 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.441195
- Iter 028 / 029, Loss: 0.438187

* Train accuracy / confusion: 79.74% / [[255, 109], [79, 485]], 
* Val   accuracy / confusion: 72.37% / [[132, 98], [65, 295]]

------------------------------ Epoch 238 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.374604
- Iter 028 / 029, Loss: 0.497436

* Train accuracy / confusion: 83.08% / [[274, 91], [66, 497]], 
* Val   accuracy / confusion: 71.19% / [[136, 94], [76, 284]]

------------------------------ Epoch 239 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.384731
- Iter 028 / 029, Loss: 0.533647

* Train accuracy / confusion: 80.82% / [[253, 107], [71, 497]], 
* Val   accuracy / confusion: 75.08% / [[142, 88], [59, 301]]

------------------------------ Epoch 240 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.232499
- Iter 028 / 029, Loss: 0.361558

* Train accuracy / confusion: 82.76% / [[270, 95], [65, 498]], 
* Val   accuracy / confusion: 74.75% / [[135, 95], [54, 306]]

------------------------------ Epoch 241 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.465575
- Iter 028 / 029, Loss: 0.396879

* Train accuracy / confusion: 82.00% / [[260, 101], [66, 501]], 
* Val   accuracy / confusion: 71.02% / [[130, 100], [71, 289]]

------------------------------ Epoch 242 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.398045
- Iter 028 / 029, Loss: 0.445105

* Train accuracy / confusion: 82.00% / [[254, 106], [61, 507]], 
* Val   accuracy / confusion: 73.56% / [[140, 90], [66, 294]]

------------------------------ Epoch 243 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.356570
- Iter 028 / 029, Loss: 0.303727

* Train accuracy / confusion: 82.11% / [[262, 99], [67, 500]], 
* Val   accuracy / confusion: 74.41% / [[133, 97], [54, 306]]

------------------------------ Epoch 244 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.674222
- Iter 028 / 029, Loss: 0.474916

* Train accuracy / confusion: 82.33% / [[261, 98], [66, 503]], 
* Val   accuracy / confusion: 73.39% / [[136, 94], [63, 297]]

------------------------------ Epoch 245 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.321479
- Iter 028 / 029, Loss: 0.304345

* Train accuracy / confusion: 81.68% / [[265, 98], [72, 493]], 
* Val   accuracy / confusion: 72.71% / [[143, 87], [74, 286]]

------------------------------ Epoch 246 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.446204
- Iter 028 / 029, Loss: 0.372905

* Train accuracy / confusion: 81.47% / [[262, 100], [72, 494]], 
* Val   accuracy / confusion: 75.08% / [[145, 85], [62, 298]]

------------------------------ Epoch 247 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.423181
- Iter 028 / 029, Loss: 0.369086

* Train accuracy / confusion: 82.44% / [[258, 104], [59, 507]], 
* Val   accuracy / confusion: 75.08% / [[136, 94], [53, 307]]

------------------------------ Epoch 248 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.382381
- Iter 028 / 029, Loss: 0.404743

* Train accuracy / confusion: 80.93% / [[253, 110], [67, 498]], 
* Val   accuracy / confusion: 74.24% / [[137, 93], [59, 301]]

------------------------------ Epoch 249 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.463575
- Iter 028 / 029, Loss: 0.422289

* Train accuracy / confusion: 81.36% / [[258, 104], [69, 497]], 
* Val   accuracy / confusion: 75.08% / [[144, 86], [61, 299]]

------------------------------ Epoch 250 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.317098
- Iter 028 / 029, Loss: 0.377977

* Train accuracy / confusion: 80.93% / [[254, 108], [69, 497]], 
* Val   accuracy / confusion: 74.75% / [[149, 81], [68, 292]]

------------------------------ Epoch 251 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.392462
- Iter 028 / 029, Loss: 0.495149

* Train accuracy / confusion: 79.74% / [[252, 112], [76, 488]], 
* Val   accuracy / confusion: 75.25% / [[155, 75], [71, 289]]

------------------------------ Epoch 252 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.550073
- Iter 028 / 029, Loss: 0.517115

* Train accuracy / confusion: 81.14% / [[254, 108], [67, 499]], 
* Val   accuracy / confusion: 73.90% / [[139, 91], [63, 297]]

------------------------------ Epoch 253 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.394454
- Iter 028 / 029, Loss: 0.488929

* Train accuracy / confusion: 83.08% / [[258, 101], [56, 513]], 
* Val   accuracy / confusion: 73.56% / [[132, 98], [58, 302]]

------------------------------ Epoch 254 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.529237
- Iter 028 / 029, Loss: 0.417212

* Train accuracy / confusion: 80.82% / [[256, 107], [71, 494]], 
* Val   accuracy / confusion: 73.56% / [[136, 94], [62, 298]]

------------------------------ Epoch 255 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.435786
- Iter 028 / 029, Loss: 0.366123

* Train accuracy / confusion: 81.68% / [[256, 106], [64, 502]], 
* Val   accuracy / confusion: 74.24% / [[149, 81], [71, 289]]

------------------------------ Epoch 256 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.399375
- Iter 028 / 029, Loss: 0.667273

* Train accuracy / confusion: 81.79% / [[260, 98], [71, 499]], 
* Val   accuracy / confusion: 71.86% / [[137, 93], [73, 287]]

------------------------------ Epoch 257 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.329478
- Iter 028 / 029, Loss: 0.470293

* Train accuracy / confusion: 83.08% / [[268, 93], [64, 503]], 
* Val   accuracy / confusion: 72.20% / [[147, 83], [81, 279]]

------------------------------ Epoch 258 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.449004
- Iter 028 / 029, Loss: 0.494499

* Train accuracy / confusion: 80.82% / [[257, 106], [72, 493]], 
* Val   accuracy / confusion: 74.24% / [[143, 87], [65, 295]]

------------------------------ Epoch 259 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.428926
- Iter 028 / 029, Loss: 0.323434

* Train accuracy / confusion: 81.57% / [[251, 108], [63, 506]], 
* Val   accuracy / confusion: 72.37% / [[133, 97], [66, 294]]

------------------------------ Epoch 260 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.315012
- Iter 028 / 029, Loss: 0.278288

* Train accuracy / confusion: 82.00% / [[256, 104], [63, 505]], 
* Val   accuracy / confusion: 74.41% / [[141, 89], [62, 298]]

------------------------------ Epoch 261 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.479479
- Iter 028 / 029, Loss: 0.438306

* Train accuracy / confusion: 81.57% / [[254, 109], [62, 503]], 
* Val   accuracy / confusion: 75.08% / [[135, 95], [52, 308]]

------------------------------ Epoch 262 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.248718
- Iter 028 / 029, Loss: 0.417217

* Train accuracy / confusion: 82.33% / [[268, 94], [70, 496]], 
* Val   accuracy / confusion: 74.41% / [[141, 89], [62, 298]]

------------------------------ Epoch 263 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.231087
- Iter 028 / 029, Loss: 0.372590

* Train accuracy / confusion: 82.22% / [[266, 96], [69, 497]], 
* Val   accuracy / confusion: 74.92% / [[141, 89], [59, 301]]

------------------------------ Epoch 264 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.303024
- Iter 028 / 029, Loss: 0.393750

* Train accuracy / confusion: 81.14% / [[259, 102], [73, 494]], 
* Val   accuracy / confusion: 73.22% / [[142, 88], [70, 290]]

------------------------------ Epoch 265 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.320704
- Iter 028 / 029, Loss: 0.377415

* Train accuracy / confusion: 82.65% / [[272, 88], [73, 495]], 
* Val   accuracy / confusion: 74.75% / [[141, 89], [60, 300]]

------------------------------ Epoch 266 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.383276
- Iter 028 / 029, Loss: 0.397758

* Train accuracy / confusion: 81.57% / [[255, 108], [63, 502]], 
* Val   accuracy / confusion: 73.56% / [[137, 93], [63, 297]]

------------------------------ Epoch 267 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.411986
- Iter 028 / 029, Loss: 0.382159

* Train accuracy / confusion: 82.11% / [[262, 98], [68, 500]], 
* Val   accuracy / confusion: 74.24% / [[146, 84], [68, 292]]

------------------------------ Epoch 268 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.744511
- Iter 028 / 029, Loss: 0.357676

* Train accuracy / confusion: 81.79% / [[265, 95], [74, 494]], 
* Val   accuracy / confusion: 75.59% / [[147, 83], [61, 299]]

------------------------------ Epoch 269 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.404542
- Iter 028 / 029, Loss: 0.545426

* Train accuracy / confusion: 81.03% / [[254, 108], [68, 498]], 
* Val   accuracy / confusion: 73.73% / [[135, 95], [60, 300]]

------------------------------ Epoch 270 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.347640
- Iter 028 / 029, Loss: 0.500181

* Train accuracy / confusion: 81.47% / [[263, 100], [72, 493]], 
* Val   accuracy / confusion: 73.05% / [[128, 102], [57, 303]]

------------------------------ Epoch 271 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.335860
- Iter 028 / 029, Loss: 0.425540

* Train accuracy / confusion: 84.05% / [[283, 81], [67, 497]], 
* Val   accuracy / confusion: 72.37% / [[125, 105], [58, 302]]

------------------------------ Epoch 272 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.409071
- Iter 028 / 029, Loss: 0.421352

* Train accuracy / confusion: 82.54% / [[263, 93], [69, 503]], 
* Val   accuracy / confusion: 73.39% / [[143, 87], [70, 290]]

------------------------------ Epoch 273 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.434837
- Iter 028 / 029, Loss: 0.348006

* Train accuracy / confusion: 82.65% / [[271, 91], [70, 496]], 
* Val   accuracy / confusion: 74.24% / [[133, 97], [55, 305]]

------------------------------ Epoch 274 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.613793
- Iter 028 / 029, Loss: 0.342916

* Train accuracy / confusion: 81.25% / [[255, 103], [71, 499]], 
* Val   accuracy / confusion: 72.88% / [[140, 90], [70, 290]]

------------------------------ Epoch 275 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.395804
- Iter 028 / 029, Loss: 0.542413

* Train accuracy / confusion: 80.06% / [[254, 110], [75, 489]], 
* Val   accuracy / confusion: 74.07% / [[139, 91], [62, 298]]

------------------------------ Epoch 276 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.469755
- Iter 028 / 029, Loss: 0.231150

* Train accuracy / confusion: 80.93% / [[262, 100], [77, 489]], 
* Val   accuracy / confusion: 73.90% / [[137, 93], [61, 299]]

------------------------------ Epoch 277 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.294869
- Iter 028 / 029, Loss: 0.299100

* Train accuracy / confusion: 82.00% / [[259, 104], [63, 502]], 
* Val   accuracy / confusion: 74.58% / [[137, 93], [57, 303]]

------------------------------ Epoch 278 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.710671
- Iter 028 / 029, Loss: 0.345702

* Train accuracy / confusion: 81.14% / [[257, 102], [73, 496]], 
* Val   accuracy / confusion: 72.54% / [[133, 97], [65, 295]]

------------------------------ Epoch 279 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.750672
- Iter 028 / 029, Loss: 0.428681

* Train accuracy / confusion: 81.25% / [[261, 103], [71, 493]], 
* Val   accuracy / confusion: 74.41% / [[148, 82], [69, 291]]

------------------------------ Epoch 280 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.365510
- Iter 028 / 029, Loss: 0.367238

* Train accuracy / confusion: 82.11% / [[267, 94], [72, 495]], 
* Val   accuracy / confusion: 74.41% / [[141, 89], [62, 298]]

------------------------------ Epoch 281 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.466812
- Iter 028 / 029, Loss: 0.339517

* Train accuracy / confusion: 80.71% / [[250, 111], [68, 499]], 
* Val   accuracy / confusion: 75.08% / [[144, 86], [61, 299]]

------------------------------ Epoch 282 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.378161
- Iter 028 / 029, Loss: 0.443349

* Train accuracy / confusion: 82.54% / [[272, 92], [70, 494]], 
* Val   accuracy / confusion: 75.25% / [[153, 77], [69, 291]]

------------------------------ Epoch 283 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.374574
- Iter 028 / 029, Loss: 0.342573

* Train accuracy / confusion: 82.44% / [[260, 97], [66, 505]], 
* Val   accuracy / confusion: 75.42% / [[144, 86], [59, 301]]

------------------------------ Epoch 284 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.661330
- Iter 028 / 029, Loss: 0.360402

* Train accuracy / confusion: 82.44% / [[268, 95], [68, 497]], 
* Val   accuracy / confusion: 72.20% / [[141, 89], [75, 285]]

------------------------------ Epoch 285 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.397526
- Iter 028 / 029, Loss: 0.482001

* Train accuracy / confusion: 81.14% / [[251, 107], [68, 502]], 
* Val   accuracy / confusion: 74.41% / [[145, 85], [66, 294]]

------------------------------ Epoch 286 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.320460
- Iter 028 / 029, Loss: 0.248434

* Train accuracy / confusion: 83.19% / [[265, 93], [63, 507]], 
* Val   accuracy / confusion: 72.88% / [[141, 89], [71, 289]]

------------------------------ Epoch 287 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.300815
- Iter 028 / 029, Loss: 0.366178

* Train accuracy / confusion: 83.30% / [[267, 93], [62, 506]], 
* Val   accuracy / confusion: 74.07% / [[136, 94], [59, 301]]

------------------------------ Epoch 288 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.415670
- Iter 028 / 029, Loss: 0.406994

* Train accuracy / confusion: 80.71% / [[252, 106], [73, 497]], 
* Val   accuracy / confusion: 72.54% / [[136, 94], [68, 292]]

------------------------------ Epoch 289 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.563677
- Iter 028 / 029, Loss: 0.312169

* Train accuracy / confusion: 81.03% / [[264, 95], [81, 488]], 
* Val   accuracy / confusion: 73.56% / [[130, 100], [56, 304]]

------------------------------ Epoch 290 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.197825
- Iter 028 / 029, Loss: 0.295744

* Train accuracy / confusion: 83.51% / [[272, 92], [61, 503]], 
* Val   accuracy / confusion: 74.07% / [[143, 87], [66, 294]]

------------------------------ Epoch 291 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.349110
- Iter 028 / 029, Loss: 0.385926

* Train accuracy / confusion: 82.54% / [[267, 97], [65, 499]], 
* Val   accuracy / confusion: 73.73% / [[138, 92], [63, 297]]

------------------------------ Epoch 292 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.450711
- Iter 028 / 029, Loss: 0.285046

* Train accuracy / confusion: 82.54% / [[263, 98], [64, 503]], 
* Val   accuracy / confusion: 74.07% / [[151, 79], [74, 286]]

------------------------------ Epoch 293 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.456495
- Iter 028 / 029, Loss: 0.365253

* Train accuracy / confusion: 83.73% / [[282, 82], [69, 495]], 
* Val   accuracy / confusion: 74.58% / [[147, 83], [67, 293]]

------------------------------ Epoch 294 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.305242
- Iter 028 / 029, Loss: 0.555290

* Train accuracy / confusion: 82.76% / [[260, 102], [58, 508]], 
* Val   accuracy / confusion: 71.36% / [[138, 92], [77, 283]]

------------------------------ Epoch 295 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.255228
- Iter 028 / 029, Loss: 0.329850

* Train accuracy / confusion: 83.62% / [[264, 100], [52, 512]], 
* Val   accuracy / confusion: 73.73% / [[143, 87], [68, 292]]

------------------------------ Epoch 296 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.279157
- Iter 028 / 029, Loss: 0.226873

* Train accuracy / confusion: 82.00% / [[268, 96], [71, 493]], 
* Val   accuracy / confusion: 74.75% / [[153, 77], [72, 288]]

------------------------------ Epoch 297 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.520353
- Iter 028 / 029, Loss: 0.247773

* Train accuracy / confusion: 80.50% / [[254, 106], [75, 493]], 
* Val   accuracy / confusion: 73.56% / [[137, 93], [63, 297]]

------------------------------ Epoch 298 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.343391
- Iter 028 / 029, Loss: 0.502420

* Train accuracy / confusion: 82.97% / [[270, 91], [67, 500]], 
* Val   accuracy / confusion: 75.42% / [[144, 86], [59, 301]]

------------------------------ Epoch 299 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.356560
- Iter 028 / 029, Loss: 0.324595

* Train accuracy / confusion: 80.50% / [[254, 108], [73, 493]], 
* Val   accuracy / confusion: 74.41% / [[154, 76], [75, 285]]

------------------------------ Epoch 300 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.325108
- Iter 028 / 029, Loss: 0.344490

* Train accuracy / confusion: 81.03% / [[256, 107], [69, 496]], 
* Val   accuracy / confusion: 74.75% / [[136, 94], [55, 305]]

------------------------------ Epoch 301 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.492291
- Iter 028 / 029, Loss: 0.310246

* Train accuracy / confusion: 82.76% / [[271, 90], [70, 497]], 
* Val   accuracy / confusion: 73.73% / [[144, 86], [69, 291]]

------------------------------ Epoch 302 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.244296
- Iter 028 / 029, Loss: 0.263494

* Train accuracy / confusion: 82.65% / [[268, 97], [64, 499]], 
* Val   accuracy / confusion: 70.85% / [[132, 98], [74, 286]]

------------------------------ Epoch 303 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.315983
- Iter 028 / 029, Loss: 0.419942

* Train accuracy / confusion: 80.93% / [[260, 103], [74, 491]], 
* Val   accuracy / confusion: 74.41% / [[145, 85], [66, 294]]

------------------------------ Epoch 304 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.561379
- Iter 028 / 029, Loss: 0.254883

* Train accuracy / confusion: 83.51% / [[262, 99], [54, 513]], 
* Val   accuracy / confusion: 73.73% / [[131, 99], [56, 304]]

------------------------------ Epoch 305 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.365644
- Iter 028 / 029, Loss: 0.598550

* Train accuracy / confusion: 82.44% / [[274, 90], [73, 491]], 
* Val   accuracy / confusion: 73.39% / [[147, 83], [74, 286]]

------------------------------ Epoch 306 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.497691
- Iter 028 / 029, Loss: 0.248090

* Train accuracy / confusion: 82.54% / [[265, 101], [61, 501]], 
* Val   accuracy / confusion: 74.41% / [[145, 85], [66, 294]]

------------------------------ Epoch 307 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.471675
- Iter 028 / 029, Loss: 0.444409

* Train accuracy / confusion: 83.08% / [[265, 94], [63, 506]], 
* Val   accuracy / confusion: 72.54% / [[138, 92], [70, 290]]

------------------------------ Epoch 308 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.422741
- Iter 028 / 029, Loss: 0.317313

* Train accuracy / confusion: 82.76% / [[266, 98], [62, 502]], 
* Val   accuracy / confusion: 74.24% / [[142, 88], [64, 296]]

------------------------------ Epoch 309 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.616941
- Iter 028 / 029, Loss: 0.375898

* Train accuracy / confusion: 82.00% / [[266, 96], [71, 495]], 
* Val   accuracy / confusion: 73.05% / [[136, 94], [65, 295]]

------------------------------ Epoch 310 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.468910
- Iter 028 / 029, Loss: 0.449264

* Train accuracy / confusion: 81.79% / [[260, 98], [71, 499]], 
* Val   accuracy / confusion: 72.03% / [[139, 91], [74, 286]]

------------------------------ Epoch 311 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.446014
- Iter 028 / 029, Loss: 0.399025

* Train accuracy / confusion: 83.84% / [[271, 88], [62, 507]], 
* Val   accuracy / confusion: 73.56% / [[135, 95], [61, 299]]

------------------------------ Epoch 312 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.373220
- Iter 028 / 029, Loss: 0.313577

* Train accuracy / confusion: 81.14% / [[260, 100], [75, 493]], 
* Val   accuracy / confusion: 73.39% / [[131, 99], [58, 302]]

------------------------------ Epoch 313 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.402473
- Iter 028 / 029, Loss: 0.543449

* Train accuracy / confusion: 82.00% / [[266, 95], [72, 495]], 
* Val   accuracy / confusion: 73.90% / [[138, 92], [62, 298]]

------------------------------ Epoch 314 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.386908
- Iter 028 / 029, Loss: 0.638304

* Train accuracy / confusion: 82.11% / [[263, 99], [67, 499]], 
* Val   accuracy / confusion: 75.42% / [[133, 97], [48, 312]]

------------------------------ Epoch 315 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.502390
- Iter 028 / 029, Loss: 0.449752

* Train accuracy / confusion: 80.82% / [[260, 103], [75, 490]], 
* Val   accuracy / confusion: 73.56% / [[138, 92], [64, 296]]

------------------------------ Epoch 316 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.315583
- Iter 028 / 029, Loss: 0.363860

* Train accuracy / confusion: 81.79% / [[270, 90], [79, 489]], 
* Val   accuracy / confusion: 71.36% / [[137, 93], [76, 284]]

------------------------------ Epoch 317 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.262527
- Iter 028 / 029, Loss: 0.489050

* Train accuracy / confusion: 81.57% / [[258, 106], [65, 499]], 
* Val   accuracy / confusion: 72.03% / [[143, 87], [78, 282]]

------------------------------ Epoch 318 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.377674
- Iter 028 / 029, Loss: 0.417116

* Train accuracy / confusion: 82.76% / [[272, 87], [73, 496]], 
* Val   accuracy / confusion: 75.59% / [[144, 86], [58, 302]]

------------------------------ Epoch 319 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.492442
- Iter 028 / 029, Loss: 0.316327

* Train accuracy / confusion: 82.33% / [[260, 102], [62, 504]], 
* Val   accuracy / confusion: 74.58% / [[145, 85], [65, 295]]

------------------------------ Epoch 320 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.326487
- Iter 028 / 029, Loss: 0.317429

* Train accuracy / confusion: 83.08% / [[272, 92], [65, 499]], 
* Val   accuracy / confusion: 72.88% / [[131, 99], [61, 299]]

------------------------------ Epoch 321 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.427779
- Iter 028 / 029, Loss: 0.551862

* Train accuracy / confusion: 83.51% / [[279, 82], [71, 496]], 
* Val   accuracy / confusion: 72.37% / [[156, 74], [89, 271]]

------------------------------ Epoch 322 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.446123
- Iter 028 / 029, Loss: 0.331299

* Train accuracy / confusion: 81.36% / [[253, 106], [67, 502]], 
* Val   accuracy / confusion: 76.61% / [[143, 87], [51, 309]]

------------------------------ Epoch 323 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.252785
- Iter 028 / 029, Loss: 0.379604

* Train accuracy / confusion: 82.00% / [[259, 104], [63, 502]], 
* Val   accuracy / confusion: 75.42% / [[136, 94], [51, 309]]

------------------------------ Epoch 324 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.367172
- Iter 028 / 029, Loss: 0.324398

* Train accuracy / confusion: 83.30% / [[272, 93], [62, 501]], 
* Val   accuracy / confusion: 72.88% / [[134, 96], [64, 296]]

------------------------------ Epoch 325 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.300369
- Iter 028 / 029, Loss: 0.225753

* Train accuracy / confusion: 83.30% / [[270, 90], [65, 503]], 
* Val   accuracy / confusion: 73.05% / [[143, 87], [72, 288]]

------------------------------ Epoch 326 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.433793
- Iter 028 / 029, Loss: 0.368305

* Train accuracy / confusion: 81.79% / [[262, 97], [72, 497]], 
* Val   accuracy / confusion: 72.71% / [[143, 87], [74, 286]]

------------------------------ Epoch 327 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.301440
- Iter 028 / 029, Loss: 0.342465

* Train accuracy / confusion: 82.33% / [[264, 95], [69, 500]], 
* Val   accuracy / confusion: 74.58% / [[146, 84], [66, 294]]

------------------------------ Epoch 328 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.652461
- Iter 028 / 029, Loss: 0.300239

* Train accuracy / confusion: 82.87% / [[264, 101], [58, 505]], 
* Val   accuracy / confusion: 74.07% / [[129, 101], [52, 308]]

------------------------------ Epoch 329 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.597035
- Iter 028 / 029, Loss: 0.329248

* Train accuracy / confusion: 82.33% / [[262, 99], [65, 502]], 
* Val   accuracy / confusion: 74.58% / [[136, 94], [56, 304]]

------------------------------ Epoch 330 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.463926
- Iter 028 / 029, Loss: 0.190719

* Train accuracy / confusion: 82.65% / [[271, 94], [67, 496]], 
* Val   accuracy / confusion: 75.25% / [[141, 89], [57, 303]]

------------------------------ Epoch 331 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.472015
- Iter 028 / 029, Loss: 0.345598

* Train accuracy / confusion: 83.41% / [[275, 86], [68, 499]], 
* Val   accuracy / confusion: 75.93% / [[144, 86], [56, 304]]

------------------------------ Epoch 332 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.427939
- Iter 028 / 029, Loss: 0.406955

* Train accuracy / confusion: 80.17% / [[253, 110], [74, 491]], 
* Val   accuracy / confusion: 74.58% / [[139, 91], [59, 301]]

------------------------------ Epoch 333 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.407258
- Iter 028 / 029, Loss: 0.415635

* Train accuracy / confusion: 81.14% / [[261, 103], [72, 492]], 
* Val   accuracy / confusion: 74.92% / [[151, 79], [69, 291]]

------------------------------ Epoch 334 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.343187
- Iter 028 / 029, Loss: 0.489969

* Train accuracy / confusion: 81.36% / [[260, 102], [71, 495]], 
* Val   accuracy / confusion: 74.24% / [[141, 89], [63, 297]]

------------------------------ Epoch 335 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.250982
- Iter 028 / 029, Loss: 0.345752

* Train accuracy / confusion: 82.44% / [[266, 97], [66, 499]], 
* Val   accuracy / confusion: 75.25% / [[150, 80], [66, 294]]

------------------------------ Epoch 336 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.268095
- Iter 028 / 029, Loss: 0.473167

* Train accuracy / confusion: 81.90% / [[258, 106], [62, 502]], 
* Val   accuracy / confusion: 73.22% / [[139, 91], [67, 293]]

------------------------------ Epoch 337 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.287134
- Iter 028 / 029, Loss: 0.351693

* Train accuracy / confusion: 83.51% / [[265, 98], [55, 510]], 
* Val   accuracy / confusion: 76.27% / [[149, 81], [59, 301]]

------------------------------ Epoch 338 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.407420
- Iter 028 / 029, Loss: 0.208462

* Train accuracy / confusion: 82.87% / [[262, 97], [62, 507]], 
* Val   accuracy / confusion: 75.25% / [[152, 78], [68, 292]]

------------------------------ Epoch 339 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.421624
- Iter 028 / 029, Loss: 0.469149

* Train accuracy / confusion: 82.44% / [[264, 95], [68, 501]], 
* Val   accuracy / confusion: 74.07% / [[144, 86], [67, 293]]

------------------------------ Epoch 340 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.376328
- Iter 028 / 029, Loss: 0.526497

* Train accuracy / confusion: 82.33% / [[267, 98], [66, 497]], 
* Val   accuracy / confusion: 74.07% / [[136, 94], [59, 301]]

------------------------------ Epoch 341 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.382890
- Iter 028 / 029, Loss: 0.507121

* Train accuracy / confusion: 83.84% / [[274, 90], [60, 504]], 
* Val   accuracy / confusion: 73.22% / [[137, 93], [65, 295]]

------------------------------ Epoch 342 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.403861
- Iter 028 / 029, Loss: 0.253060

* Train accuracy / confusion: 82.22% / [[268, 90], [75, 495]], 
* Val   accuracy / confusion: 73.56% / [[143, 87], [69, 291]]

------------------------------ Epoch 343 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.305795
- Iter 028 / 029, Loss: 0.355011

* Train accuracy / confusion: 81.68% / [[263, 100], [70, 495]], 
* Val   accuracy / confusion: 72.54% / [[134, 96], [66, 294]]

------------------------------ Epoch 344 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.267009
- Iter 028 / 029, Loss: 0.337394

* Train accuracy / confusion: 81.90% / [[261, 100], [68, 499]], 
* Val   accuracy / confusion: 75.42% / [[137, 93], [52, 308]]

------------------------------ Epoch 345 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.481018
- Iter 028 / 029, Loss: 0.362971

* Train accuracy / confusion: 84.05% / [[282, 81], [67, 498]], 
* Val   accuracy / confusion: 74.24% / [[151, 79], [73, 287]]

------------------------------ Epoch 346 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.366798
- Iter 028 / 029, Loss: 0.447629

* Train accuracy / confusion: 82.65% / [[265, 97], [64, 502]], 
* Val   accuracy / confusion: 73.73% / [[144, 86], [69, 291]]

------------------------------ Epoch 347 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.718011
- Iter 028 / 029, Loss: 0.369339

* Train accuracy / confusion: 82.11% / [[263, 101], [65, 499]], 
* Val   accuracy / confusion: 74.07% / [[143, 87], [66, 294]]

------------------------------ Epoch 348 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.542391
- Iter 028 / 029, Loss: 0.535678

* Train accuracy / confusion: 81.90% / [[266, 92], [76, 494]], 
* Val   accuracy / confusion: 74.41% / [[147, 83], [68, 292]]

------------------------------ Epoch 349 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.329353
- Iter 028 / 029, Loss: 0.389588

* Train accuracy / confusion: 81.25% / [[262, 103], [71, 492]], 
* Val   accuracy / confusion: 72.37% / [[136, 94], [69, 291]]

------------------------------ Epoch 350 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.288106
- Iter 028 / 029, Loss: 0.249224

* Train accuracy / confusion: 84.59% / [[270, 93], [50, 515]], 
* Val   accuracy / confusion: 75.59% / [[143, 87], [57, 303]]

------------------------------ Epoch 351 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.361662
- Iter 028 / 029, Loss: 0.471099

* Train accuracy / confusion: 82.22% / [[268, 97], [68, 495]], 
* Val   accuracy / confusion: 71.02% / [[141, 89], [82, 278]]

------------------------------ Epoch 352 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.501525
- Iter 028 / 029, Loss: 0.331133

* Train accuracy / confusion: 82.87% / [[269, 90], [69, 500]], 
* Val   accuracy / confusion: 73.90% / [[144, 86], [68, 292]]

------------------------------ Epoch 353 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.407159
- Iter 028 / 029, Loss: 0.279026

* Train accuracy / confusion: 81.79% / [[264, 98], [71, 495]], 
* Val   accuracy / confusion: 73.90% / [[146, 84], [70, 290]]

------------------------------ Epoch 354 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.380334
- Iter 028 / 029, Loss: 0.466162

* Train accuracy / confusion: 82.33% / [[271, 96], [68, 493]], 
* Val   accuracy / confusion: 74.75% / [[141, 89], [60, 300]]

------------------------------ Epoch 355 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.286727
- Iter 028 / 029, Loss: 0.304201

* Train accuracy / confusion: 83.73% / [[264, 97], [54, 513]], 
* Val   accuracy / confusion: 74.92% / [[141, 89], [59, 301]]

------------------------------ Epoch 356 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.333764
- Iter 028 / 029, Loss: 0.292459

* Train accuracy / confusion: 82.76% / [[272, 93], [67, 496]], 
* Val   accuracy / confusion: 73.22% / [[139, 91], [67, 293]]

------------------------------ Epoch 357 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.400503
- Iter 028 / 029, Loss: 0.487848

* Train accuracy / confusion: 84.16% / [[271, 91], [56, 510]], 
* Val   accuracy / confusion: 74.24% / [[128, 102], [50, 310]]

------------------------------ Epoch 358 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.466222
- Iter 028 / 029, Loss: 0.427533

* Train accuracy / confusion: 83.51% / [[273, 90], [63, 502]], 
* Val   accuracy / confusion: 74.07% / [[146, 84], [69, 291]]

------------------------------ Epoch 359 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.426810
- Iter 028 / 029, Loss: 0.355535

* Train accuracy / confusion: 82.22% / [[266, 95], [70, 497]], 
* Val   accuracy / confusion: 74.41% / [[154, 76], [75, 285]]

------------------------------ Epoch 360 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.280633
- Iter 028 / 029, Loss: 0.236516

* Train accuracy / confusion: 83.62% / [[271, 88], [64, 505]], 
* Val   accuracy / confusion: 75.93% / [[144, 86], [56, 304]]

------------------------------ Epoch 361 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.471954
- Iter 028 / 029, Loss: 0.349577

* Train accuracy / confusion: 82.65% / [[271, 92], [69, 496]], 
* Val   accuracy / confusion: 71.02% / [[149, 81], [90, 270]]

------------------------------ Epoch 362 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.314676
- Iter 028 / 029, Loss: 0.425253

* Train accuracy / confusion: 83.84% / [[276, 87], [63, 502]], 
* Val   accuracy / confusion: 73.22% / [[147, 83], [75, 285]]

------------------------------ Epoch 363 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.295172
- Iter 028 / 029, Loss: 0.228556

* Train accuracy / confusion: 83.19% / [[270, 92], [64, 502]], 
* Val   accuracy / confusion: 74.58% / [[143, 87], [63, 297]]

------------------------------ Epoch 364 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.239452
- Iter 028 / 029, Loss: 0.320207

* Train accuracy / confusion: 82.65% / [[268, 92], [69, 499]], 
* Val   accuracy / confusion: 73.90% / [[142, 88], [66, 294]]

------------------------------ Epoch 365 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.415354
- Iter 028 / 029, Loss: 0.367325

* Train accuracy / confusion: 81.68% / [[265, 98], [72, 493]], 
* Val   accuracy / confusion: 74.41% / [[149, 81], [70, 290]]

------------------------------ Epoch 366 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.367193
- Iter 028 / 029, Loss: 0.391268

* Train accuracy / confusion: 82.22% / [[265, 100], [65, 498]], 
* Val   accuracy / confusion: 73.73% / [[135, 95], [60, 300]]

------------------------------ Epoch 367 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.291423
- Iter 028 / 029, Loss: 0.336925

* Train accuracy / confusion: 81.47% / [[261, 101], [71, 495]], 
* Val   accuracy / confusion: 71.53% / [[125, 105], [63, 297]]

------------------------------ Epoch 368 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.262772
- Iter 028 / 029, Loss: 0.535493

* Train accuracy / confusion: 83.08% / [[273, 89], [68, 498]], 
* Val   accuracy / confusion: 74.58% / [[144, 86], [64, 296]]

------------------------------ Epoch 369 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.372668
- Iter 028 / 029, Loss: 0.277680

* Train accuracy / confusion: 82.11% / [[265, 95], [71, 497]], 
* Val   accuracy / confusion: 72.37% / [[145, 85], [78, 282]]

------------------------------ Epoch 370 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.379174
- Iter 028 / 029, Loss: 0.432099

* Train accuracy / confusion: 83.08% / [[264, 96], [61, 507]], 
* Val   accuracy / confusion: 72.71% / [[137, 93], [68, 292]]

------------------------------ Epoch 371 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.268536
- Iter 028 / 029, Loss: 0.424520

* Train accuracy / confusion: 82.97% / [[268, 95], [63, 502]], 
* Val   accuracy / confusion: 74.24% / [[141, 89], [63, 297]]

------------------------------ Epoch 372 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.293233
- Iter 028 / 029, Loss: 0.368883

* Train accuracy / confusion: 83.19% / [[269, 93], [63, 503]], 
* Val   accuracy / confusion: 73.39% / [[139, 91], [66, 294]]

------------------------------ Epoch 373 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.442047
- Iter 028 / 029, Loss: 0.486380

* Train accuracy / confusion: 82.22% / [[268, 92], [73, 495]], 
* Val   accuracy / confusion: 73.73% / [[144, 86], [69, 291]]

------------------------------ Epoch 374 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.430139
- Iter 028 / 029, Loss: 0.400584

* Train accuracy / confusion: 82.11% / [[267, 98], [68, 495]], 
* Val   accuracy / confusion: 73.05% / [[138, 92], [67, 293]]

------------------------------ Epoch 375 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.552635
- Iter 028 / 029, Loss: 0.356829

* Train accuracy / confusion: 80.50% / [[248, 113], [68, 499]], 
* Val   accuracy / confusion: 72.20% / [[140, 90], [74, 286]]

------------------------------ Epoch 376 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.291544
- Iter 028 / 029, Loss: 0.412075

* Train accuracy / confusion: 85.13% / [[275, 86], [52, 515]], 
* Val   accuracy / confusion: 73.90% / [[136, 94], [60, 300]]

------------------------------ Epoch 377 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.359077
- Iter 028 / 029, Loss: 0.287259

* Train accuracy / confusion: 84.27% / [[270, 91], [55, 512]], 
* Val   accuracy / confusion: 73.90% / [[139, 91], [63, 297]]

------------------------------ Epoch 378 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.396199
- Iter 028 / 029, Loss: 0.397641

* Train accuracy / confusion: 82.97% / [[264, 98], [60, 506]], 
* Val   accuracy / confusion: 71.53% / [[126, 104], [64, 296]]

------------------------------ Epoch 379 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.452631
- Iter 028 / 029, Loss: 0.416855

* Train accuracy / confusion: 83.19% / [[274, 92], [64, 498]], 
* Val   accuracy / confusion: 73.22% / [[140, 90], [68, 292]]

------------------------------ Epoch 380 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.588578
- Iter 028 / 029, Loss: 0.461994

* Train accuracy / confusion: 83.94% / [[280, 85], [64, 499]], 
* Val   accuracy / confusion: 74.58% / [[140, 90], [60, 300]]

------------------------------ Epoch 381 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.441516
- Iter 028 / 029, Loss: 0.416744

* Train accuracy / confusion: 82.54% / [[266, 97], [65, 500]], 
* Val   accuracy / confusion: 75.59% / [[144, 86], [58, 302]]

------------------------------ Epoch 382 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.582318
- Iter 028 / 029, Loss: 0.700882

* Train accuracy / confusion: 82.65% / [[269, 93], [68, 498]], 
* Val   accuracy / confusion: 73.39% / [[144, 86], [71, 289]]

------------------------------ Epoch 383 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.390024
- Iter 028 / 029, Loss: 0.462781

* Train accuracy / confusion: 82.44% / [[263, 102], [61, 502]], 
* Val   accuracy / confusion: 72.20% / [[129, 101], [63, 297]]

------------------------------ Epoch 384 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.366930
- Iter 028 / 029, Loss: 0.281275

* Train accuracy / confusion: 81.90% / [[267, 97], [71, 493]], 
* Val   accuracy / confusion: 72.37% / [[142, 88], [75, 285]]

------------------------------ Epoch 385 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.436013
- Iter 028 / 029, Loss: 0.402559

* Train accuracy / confusion: 82.54% / [[263, 95], [67, 503]], 
* Val   accuracy / confusion: 75.08% / [[146, 84], [63, 297]]

------------------------------ Epoch 386 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.301831
- Iter 028 / 029, Loss: 0.388130

* Train accuracy / confusion: 82.87% / [[263, 100], [59, 506]], 
* Val   accuracy / confusion: 73.39% / [[135, 95], [62, 298]]

------------------------------ Epoch 387 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.514098
- Iter 028 / 029, Loss: 0.259812

* Train accuracy / confusion: 82.87% / [[262, 101], [58, 507]], 
* Val   accuracy / confusion: 73.56% / [[135, 95], [61, 299]]

------------------------------ Epoch 388 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.353788
- Iter 028 / 029, Loss: 0.320602

* Train accuracy / confusion: 82.44% / [[266, 96], [67, 499]], 
* Val   accuracy / confusion: 72.03% / [[141, 89], [76, 284]]

------------------------------ Epoch 389 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.395485
- Iter 028 / 029, Loss: 0.418343

* Train accuracy / confusion: 82.11% / [[262, 100], [66, 500]], 
* Val   accuracy / confusion: 73.39% / [[130, 100], [57, 303]]

------------------------------ Epoch 390 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.353766
- Iter 028 / 029, Loss: 0.257830

* Train accuracy / confusion: 83.62% / [[266, 92], [60, 510]], 
* Val   accuracy / confusion: 72.37% / [[131, 99], [64, 296]]

------------------------------ Epoch 391 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.261809
- Iter 028 / 029, Loss: 0.653701

* Train accuracy / confusion: 82.87% / [[270, 92], [67, 499]], 
* Val   accuracy / confusion: 73.73% / [[144, 86], [69, 291]]

------------------------------ Epoch 392 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.420760
- Iter 028 / 029, Loss: 0.286159

* Train accuracy / confusion: 82.33% / [[267, 96], [68, 497]], 
* Val   accuracy / confusion: 73.73% / [[133, 97], [58, 302]]

------------------------------ Epoch 393 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.374815
- Iter 028 / 029, Loss: 0.334971

* Train accuracy / confusion: 82.54% / [[264, 97], [65, 502]], 
* Val   accuracy / confusion: 73.73% / [[137, 93], [62, 298]]

------------------------------ Epoch 394 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.373435
- Iter 028 / 029, Loss: 0.390772

* Train accuracy / confusion: 82.65% / [[265, 97], [64, 502]], 
* Val   accuracy / confusion: 73.56% / [[136, 94], [62, 298]]

------------------------------ Epoch 395 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.372248
- Iter 028 / 029, Loss: 0.345174

* Train accuracy / confusion: 83.41% / [[279, 84], [70, 495]], 
* Val   accuracy / confusion: 73.22% / [[149, 81], [77, 283]]

------------------------------ Epoch 396 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.463446
- Iter 028 / 029, Loss: 0.247772

* Train accuracy / confusion: 81.25% / [[262, 100], [74, 492]], 
* Val   accuracy / confusion: 73.05% / [[138, 92], [67, 293]]

------------------------------ Epoch 397 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.306840
- Iter 028 / 029, Loss: 0.263249

* Train accuracy / confusion: 81.90% / [[262, 101], [67, 498]], 
* Val   accuracy / confusion: 73.05% / [[143, 87], [72, 288]]

------------------------------ Epoch 398 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.325769
- Iter 028 / 029, Loss: 0.322970

* Train accuracy / confusion: 82.54% / [[261, 99], [63, 505]], 
* Val   accuracy / confusion: 73.39% / [[142, 88], [69, 291]]

------------------------------ Epoch 399 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.295122
- Iter 028 / 029, Loss: 0.399755

* Train accuracy / confusion: 84.16% / [[271, 89], [58, 510]], 
* Val   accuracy / confusion: 75.76% / [[147, 83], [60, 300]]

------------------------------ Epoch 400 / 500, Learning rate: 9.56e-04 ------------------------------
- Iter 014 / 029, Loss: 0.282597
- Iter 028 / 029, Loss: 0.404008

* Train accuracy / confusion: 81.47% / [[260, 104], [68, 496]], 
* Val   accuracy / confusion: 72.03% / [[138, 92], [73, 287]]

------------------------------ Epoch 401 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.529050
- Iter 028 / 029, Loss: 0.312400

* Train accuracy / confusion: 82.00% / [[269, 91], [76, 492]], 
* Val   accuracy / confusion: 75.42% / [[133, 97], [48, 312]]

------------------------------ Epoch 402 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.393908
- Iter 028 / 029, Loss: 0.462052

* Train accuracy / confusion: 82.65% / [[265, 95], [66, 502]], 
* Val   accuracy / confusion: 76.44% / [[137, 93], [46, 314]]

------------------------------ Epoch 403 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.192966
- Iter 028 / 029, Loss: 0.648361

* Train accuracy / confusion: 82.87% / [[279, 83], [76, 490]], 
* Val   accuracy / confusion: 73.90% / [[147, 83], [71, 289]]

------------------------------ Epoch 404 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.268693
- Iter 028 / 029, Loss: 0.319013

* Train accuracy / confusion: 82.44% / [[266, 93], [70, 499]], 
* Val   accuracy / confusion: 73.22% / [[139, 91], [67, 293]]

------------------------------ Epoch 405 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.464756
- Iter 028 / 029, Loss: 0.520996

* Train accuracy / confusion: 82.76% / [[272, 89], [71, 496]], 
* Val   accuracy / confusion: 73.73% / [[143, 87], [68, 292]]

------------------------------ Epoch 406 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.424488
- Iter 028 / 029, Loss: 0.532073

* Train accuracy / confusion: 81.36% / [[265, 98], [75, 490]], 
* Val   accuracy / confusion: 73.39% / [[137, 93], [64, 296]]

------------------------------ Epoch 407 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.288462
- Iter 028 / 029, Loss: 0.316404

* Train accuracy / confusion: 82.97% / [[271, 88], [70, 499]], 
* Val   accuracy / confusion: 72.37% / [[133, 97], [66, 294]]

------------------------------ Epoch 408 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.311412
- Iter 028 / 029, Loss: 0.417052

* Train accuracy / confusion: 83.30% / [[274, 88], [67, 499]], 
* Val   accuracy / confusion: 73.73% / [[142, 88], [67, 293]]

------------------------------ Epoch 409 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.300107
- Iter 028 / 029, Loss: 0.340573

* Train accuracy / confusion: 83.41% / [[272, 92], [62, 502]], 
* Val   accuracy / confusion: 75.59% / [[143, 87], [57, 303]]

------------------------------ Epoch 410 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.363429
- Iter 028 / 029, Loss: 0.372153

* Train accuracy / confusion: 81.68% / [[262, 101], [69, 496]], 
* Val   accuracy / confusion: 73.05% / [[139, 91], [68, 292]]

------------------------------ Epoch 411 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.369273
- Iter 028 / 029, Loss: 0.360471

* Train accuracy / confusion: 82.87% / [[270, 93], [66, 499]], 
* Val   accuracy / confusion: 74.07% / [[149, 81], [72, 288]]

------------------------------ Epoch 412 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.305896
- Iter 028 / 029, Loss: 0.384959

* Train accuracy / confusion: 81.79% / [[251, 109], [60, 508]], 
* Val   accuracy / confusion: 72.20% / [[133, 97], [67, 293]]

------------------------------ Epoch 413 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.389282
- Iter 028 / 029, Loss: 0.329815

* Train accuracy / confusion: 83.30% / [[275, 87], [68, 498]], 
* Val   accuracy / confusion: 76.27% / [[141, 89], [51, 309]]

------------------------------ Epoch 414 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.279755
- Iter 028 / 029, Loss: 0.380743

* Train accuracy / confusion: 81.47% / [[260, 102], [70, 496]], 
* Val   accuracy / confusion: 76.27% / [[145, 85], [55, 305]]

------------------------------ Epoch 415 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.453851
- Iter 028 / 029, Loss: 0.479612

* Train accuracy / confusion: 82.97% / [[266, 93], [65, 504]], 
* Val   accuracy / confusion: 73.90% / [[139, 91], [63, 297]]

------------------------------ Epoch 416 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.406931
- Iter 028 / 029, Loss: 0.427120

* Train accuracy / confusion: 80.93% / [[263, 96], [81, 488]], 
* Val   accuracy / confusion: 74.07% / [[144, 86], [67, 293]]

------------------------------ Epoch 417 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.233580
- Iter 028 / 029, Loss: 0.606566

* Train accuracy / confusion: 84.27% / [[275, 82], [64, 507]], 
* Val   accuracy / confusion: 74.07% / [[141, 89], [64, 296]]

------------------------------ Epoch 418 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.381772
- Iter 028 / 029, Loss: 0.641457

* Train accuracy / confusion: 81.36% / [[263, 101], [72, 492]], 
* Val   accuracy / confusion: 74.58% / [[134, 96], [54, 306]]

------------------------------ Epoch 419 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.193346
- Iter 028 / 029, Loss: 0.481310

* Train accuracy / confusion: 82.65% / [[261, 103], [58, 506]], 
* Val   accuracy / confusion: 73.05% / [[132, 98], [61, 299]]

------------------------------ Epoch 420 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.406663
- Iter 028 / 029, Loss: 0.496289

* Train accuracy / confusion: 82.00% / [[269, 92], [75, 492]], 
* Val   accuracy / confusion: 75.08% / [[148, 82], [65, 295]]

------------------------------ Epoch 421 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.275003
- Iter 028 / 029, Loss: 0.246395

* Train accuracy / confusion: 81.25% / [[260, 100], [74, 494]], 
* Val   accuracy / confusion: 74.24% / [[139, 91], [61, 299]]

------------------------------ Epoch 422 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.344546
- Iter 028 / 029, Loss: 0.408716

* Train accuracy / confusion: 82.65% / [[264, 95], [66, 503]], 
* Val   accuracy / confusion: 73.22% / [[135, 95], [63, 297]]

------------------------------ Epoch 423 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.397077
- Iter 028 / 029, Loss: 0.451938

* Train accuracy / confusion: 81.90% / [[265, 99], [69, 495]], 
* Val   accuracy / confusion: 75.76% / [[143, 87], [56, 304]]

------------------------------ Epoch 424 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.195653
- Iter 028 / 029, Loss: 0.373730

* Train accuracy / confusion: 81.68% / [[263, 97], [73, 495]], 
* Val   accuracy / confusion: 74.58% / [[144, 86], [64, 296]]

------------------------------ Epoch 425 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.360116
- Iter 028 / 029, Loss: 0.219056

* Train accuracy / confusion: 82.11% / [[266, 99], [67, 496]], 
* Val   accuracy / confusion: 74.24% / [[139, 91], [61, 299]]

------------------------------ Epoch 426 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.537256
- Iter 028 / 029, Loss: 0.444198

* Train accuracy / confusion: 82.54% / [[265, 97], [65, 501]], 
* Val   accuracy / confusion: 73.90% / [[139, 91], [63, 297]]

------------------------------ Epoch 427 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.319713
- Iter 028 / 029, Loss: 0.362802

* Train accuracy / confusion: 83.51% / [[271, 92], [61, 504]], 
* Val   accuracy / confusion: 74.24% / [[139, 91], [61, 299]]

------------------------------ Epoch 428 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.467483
- Iter 028 / 029, Loss: 0.608673

* Train accuracy / confusion: 81.47% / [[263, 96], [76, 493]], 
* Val   accuracy / confusion: 72.71% / [[137, 93], [68, 292]]

------------------------------ Epoch 429 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.257080
- Iter 028 / 029, Loss: 0.317332

* Train accuracy / confusion: 84.70% / [[274, 88], [54, 512]], 
* Val   accuracy / confusion: 74.92% / [[149, 81], [67, 293]]

------------------------------ Epoch 430 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.332734
- Iter 028 / 029, Loss: 0.432906

* Train accuracy / confusion: 84.16% / [[277, 87], [60, 504]], 
* Val   accuracy / confusion: 74.24% / [[140, 90], [62, 298]]

------------------------------ Epoch 431 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.390977
- Iter 028 / 029, Loss: 0.458553

* Train accuracy / confusion: 83.08% / [[271, 91], [66, 500]], 
* Val   accuracy / confusion: 75.76% / [[141, 89], [54, 306]]

------------------------------ Epoch 432 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.384990
- Iter 028 / 029, Loss: 0.165437

* Train accuracy / confusion: 82.00% / [[264, 96], [71, 497]], 
* Val   accuracy / confusion: 75.25% / [[144, 86], [60, 300]]

------------------------------ Epoch 433 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.623936
- Iter 028 / 029, Loss: 0.378977

* Train accuracy / confusion: 81.90% / [[257, 106], [62, 503]], 
* Val   accuracy / confusion: 76.10% / [[146, 84], [57, 303]]

------------------------------ Epoch 434 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.388748
- Iter 028 / 029, Loss: 0.598940

* Train accuracy / confusion: 83.94% / [[267, 94], [55, 512]], 
* Val   accuracy / confusion: 72.71% / [[129, 101], [60, 300]]

------------------------------ Epoch 435 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.298271
- Iter 028 / 029, Loss: 0.218553

* Train accuracy / confusion: 82.97% / [[260, 99], [59, 510]], 
* Val   accuracy / confusion: 73.56% / [[138, 92], [64, 296]]

------------------------------ Epoch 436 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.608496
- Iter 028 / 029, Loss: 0.350094

* Train accuracy / confusion: 82.65% / [[268, 96], [65, 499]], 
* Val   accuracy / confusion: 72.37% / [[127, 103], [60, 300]]

------------------------------ Epoch 437 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.440001
- Iter 028 / 029, Loss: 0.357553

* Train accuracy / confusion: 81.57% / [[255, 103], [68, 502]], 
* Val   accuracy / confusion: 74.58% / [[144, 86], [64, 296]]

------------------------------ Epoch 438 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.350488
- Iter 028 / 029, Loss: 0.349315

* Train accuracy / confusion: 82.44% / [[264, 97], [66, 501]], 
* Val   accuracy / confusion: 74.92% / [[140, 90], [58, 302]]

------------------------------ Epoch 439 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.503910
- Iter 028 / 029, Loss: 0.437923

* Train accuracy / confusion: 82.76% / [[273, 91], [69, 495]], 
* Val   accuracy / confusion: 74.07% / [[138, 92], [61, 299]]

------------------------------ Epoch 440 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.534366
- Iter 028 / 029, Loss: 0.426392

* Train accuracy / confusion: 81.68% / [[268, 97], [73, 490]], 
* Val   accuracy / confusion: 73.90% / [[143, 87], [67, 293]]

------------------------------ Epoch 441 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.464827
- Iter 028 / 029, Loss: 0.414302

* Train accuracy / confusion: 82.44% / [[262, 101], [62, 503]], 
* Val   accuracy / confusion: 75.76% / [[132, 98], [45, 315]]

------------------------------ Epoch 442 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.432141
- Iter 028 / 029, Loss: 0.513496

* Train accuracy / confusion: 83.84% / [[278, 89], [61, 500]], 
* Val   accuracy / confusion: 74.24% / [[143, 87], [65, 295]]

------------------------------ Epoch 443 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.510019
- Iter 028 / 029, Loss: 0.261024

* Train accuracy / confusion: 82.11% / [[262, 100], [66, 500]], 
* Val   accuracy / confusion: 73.56% / [[141, 89], [67, 293]]

------------------------------ Epoch 444 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.422362
- Iter 028 / 029, Loss: 0.408540

* Train accuracy / confusion: 84.59% / [[268, 91], [52, 517]], 
* Val   accuracy / confusion: 76.10% / [[148, 82], [59, 301]]

------------------------------ Epoch 445 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.265767
- Iter 028 / 029, Loss: 0.447463

* Train accuracy / confusion: 83.19% / [[271, 90], [66, 501]], 
* Val   accuracy / confusion: 74.07% / [[140, 90], [63, 297]]

------------------------------ Epoch 446 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.333814
- Iter 028 / 029, Loss: 0.451772

* Train accuracy / confusion: 83.19% / [[274, 86], [70, 498]], 
* Val   accuracy / confusion: 73.90% / [[139, 91], [63, 297]]

------------------------------ Epoch 447 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.394690
- Iter 028 / 029, Loss: 0.338153

* Train accuracy / confusion: 82.44% / [[270, 92], [71, 495]], 
* Val   accuracy / confusion: 74.07% / [[139, 91], [62, 298]]

------------------------------ Epoch 448 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.440739
- Iter 028 / 029, Loss: 0.238788

* Train accuracy / confusion: 81.79% / [[263, 99], [70, 496]], 
* Val   accuracy / confusion: 75.08% / [[141, 89], [58, 302]]

------------------------------ Epoch 449 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.407008
- Iter 028 / 029, Loss: 0.354595

* Train accuracy / confusion: 83.41% / [[270, 92], [62, 504]], 
* Val   accuracy / confusion: 72.54% / [[141, 89], [73, 287]]

------------------------------ Epoch 450 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.263445
- Iter 028 / 029, Loss: 0.402553

* Train accuracy / confusion: 83.51% / [[276, 85], [68, 499]], 
* Val   accuracy / confusion: 71.86% / [[135, 95], [71, 289]]

------------------------------ Epoch 451 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.225311
- Iter 028 / 029, Loss: 0.607630

* Train accuracy / confusion: 82.97% / [[269, 92], [66, 501]], 
* Val   accuracy / confusion: 72.20% / [[139, 91], [73, 287]]

------------------------------ Epoch 452 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.247698
- Iter 028 / 029, Loss: 0.306980

* Train accuracy / confusion: 82.22% / [[266, 98], [67, 497]], 
* Val   accuracy / confusion: 75.25% / [[152, 78], [68, 292]]

------------------------------ Epoch 453 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.330668
- Iter 028 / 029, Loss: 0.380760

* Train accuracy / confusion: 82.22% / [[270, 93], [72, 493]], 
* Val   accuracy / confusion: 73.73% / [[142, 88], [67, 293]]

------------------------------ Epoch 454 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.382459
- Iter 028 / 029, Loss: 0.556243

* Train accuracy / confusion: 82.97% / [[273, 89], [69, 497]], 
* Val   accuracy / confusion: 73.73% / [[145, 85], [70, 290]]

------------------------------ Epoch 455 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.330673
- Iter 028 / 029, Loss: 0.260246

* Train accuracy / confusion: 83.51% / [[271, 89], [64, 504]], 
* Val   accuracy / confusion: 74.24% / [[148, 82], [70, 290]]

------------------------------ Epoch 456 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.283479
- Iter 028 / 029, Loss: 0.413986

* Train accuracy / confusion: 83.30% / [[276, 90], [65, 497]], 
* Val   accuracy / confusion: 74.41% / [[146, 84], [67, 293]]

------------------------------ Epoch 457 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.588723
- Iter 028 / 029, Loss: 0.473537

* Train accuracy / confusion: 83.84% / [[275, 87], [63, 503]], 
* Val   accuracy / confusion: 75.25% / [[152, 78], [68, 292]]

------------------------------ Epoch 458 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.500765
- Iter 028 / 029, Loss: 0.282313

* Train accuracy / confusion: 81.57% / [[263, 96], [75, 494]], 
* Val   accuracy / confusion: 75.08% / [[144, 86], [61, 299]]

------------------------------ Epoch 459 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.363853
- Iter 028 / 029, Loss: 0.335262

* Train accuracy / confusion: 82.76% / [[269, 94], [66, 499]], 
* Val   accuracy / confusion: 73.56% / [[133, 97], [59, 301]]

------------------------------ Epoch 460 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.474168
- Iter 028 / 029, Loss: 0.386715

* Train accuracy / confusion: 81.57% / [[257, 105], [66, 500]], 
* Val   accuracy / confusion: 75.08% / [[155, 75], [72, 288]]

------------------------------ Epoch 461 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.333104
- Iter 028 / 029, Loss: 0.396741

* Train accuracy / confusion: 82.00% / [[261, 100], [67, 500]], 
* Val   accuracy / confusion: 73.22% / [[138, 92], [66, 294]]

------------------------------ Epoch 462 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.479610
- Iter 028 / 029, Loss: 0.314411

* Train accuracy / confusion: 81.68% / [[260, 99], [71, 498]], 
* Val   accuracy / confusion: 73.56% / [[144, 86], [70, 290]]

------------------------------ Epoch 463 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.608063
- Iter 028 / 029, Loss: 0.291349

* Train accuracy / confusion: 82.44% / [[262, 96], [67, 503]], 
* Val   accuracy / confusion: 73.56% / [[144, 86], [70, 290]]

------------------------------ Epoch 464 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.551078
- Iter 028 / 029, Loss: 0.335876

* Train accuracy / confusion: 81.03% / [[259, 104], [72, 493]], 
* Val   accuracy / confusion: 74.75% / [[145, 85], [64, 296]]

------------------------------ Epoch 465 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.411474
- Iter 028 / 029, Loss: 0.450492

* Train accuracy / confusion: 82.87% / [[276, 90], [69, 493]], 
* Val   accuracy / confusion: 72.88% / [[130, 100], [60, 300]]

------------------------------ Epoch 466 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.390342
- Iter 028 / 029, Loss: 0.394533

* Train accuracy / confusion: 80.82% / [[262, 102], [76, 488]], 
* Val   accuracy / confusion: 76.44% / [[141, 89], [50, 310]]

------------------------------ Epoch 467 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.457486
- Iter 028 / 029, Loss: 0.350249

* Train accuracy / confusion: 83.41% / [[275, 89], [65, 499]], 
* Val   accuracy / confusion: 73.22% / [[140, 90], [68, 292]]

------------------------------ Epoch 468 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.345736
- Iter 028 / 029, Loss: 0.431703

* Train accuracy / confusion: 83.73% / [[270, 94], [57, 507]], 
* Val   accuracy / confusion: 74.58% / [[132, 98], [52, 308]]

------------------------------ Epoch 469 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.364855
- Iter 028 / 029, Loss: 0.674126

* Train accuracy / confusion: 82.87% / [[271, 94], [65, 498]], 
* Val   accuracy / confusion: 74.58% / [[141, 89], [61, 299]]

------------------------------ Epoch 470 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.391441
- Iter 028 / 029, Loss: 0.281189

* Train accuracy / confusion: 83.73% / [[276, 89], [62, 501]], 
* Val   accuracy / confusion: 73.39% / [[137, 93], [64, 296]]

------------------------------ Epoch 471 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.520606
- Iter 028 / 029, Loss: 0.531157

* Train accuracy / confusion: 82.33% / [[267, 95], [69, 497]], 
* Val   accuracy / confusion: 74.75% / [[135, 95], [54, 306]]

------------------------------ Epoch 472 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.401080
- Iter 028 / 029, Loss: 0.381243

* Train accuracy / confusion: 82.44% / [[267, 95], [68, 498]], 
* Val   accuracy / confusion: 74.58% / [[147, 83], [67, 293]]

------------------------------ Epoch 473 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.399257
- Iter 028 / 029, Loss: 0.485151

* Train accuracy / confusion: 82.44% / [[272, 90], [73, 493]], 
* Val   accuracy / confusion: 74.75% / [[142, 88], [61, 299]]

------------------------------ Epoch 474 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.538056
- Iter 028 / 029, Loss: 0.227767

* Train accuracy / confusion: 83.30% / [[273, 89], [66, 500]], 
* Val   accuracy / confusion: 73.22% / [[144, 86], [72, 288]]

------------------------------ Epoch 475 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.376695
- Iter 028 / 029, Loss: 0.246048

* Train accuracy / confusion: 82.22% / [[270, 90], [75, 493]], 
* Val   accuracy / confusion: 74.41% / [[138, 92], [59, 301]]

------------------------------ Epoch 476 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.633906
- Iter 028 / 029, Loss: 0.504001

* Train accuracy / confusion: 81.14% / [[255, 105], [70, 498]], 
* Val   accuracy / confusion: 73.39% / [[142, 88], [69, 291]]

------------------------------ Epoch 477 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.304998
- Iter 028 / 029, Loss: 0.290524

* Train accuracy / confusion: 82.11% / [[274, 92], [74, 488]], 
* Val   accuracy / confusion: 72.37% / [[133, 97], [66, 294]]

------------------------------ Epoch 478 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.538577
- Iter 028 / 029, Loss: 0.652294

* Train accuracy / confusion: 83.84% / [[279, 86], [64, 499]], 
* Val   accuracy / confusion: 73.56% / [[136, 94], [62, 298]]

------------------------------ Epoch 479 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.240559
- Iter 028 / 029, Loss: 0.396842

* Train accuracy / confusion: 81.47% / [[259, 103], [69, 497]], 
* Val   accuracy / confusion: 74.58% / [[145, 85], [65, 295]]

------------------------------ Epoch 480 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.375484
- Iter 028 / 029, Loss: 0.284796

* Train accuracy / confusion: 82.65% / [[266, 93], [68, 501]], 
* Val   accuracy / confusion: 74.41% / [[142, 88], [63, 297]]

------------------------------ Epoch 481 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.341561
- Iter 028 / 029, Loss: 0.460577

* Train accuracy / confusion: 82.87% / [[267, 96], [63, 502]], 
* Val   accuracy / confusion: 75.76% / [[144, 86], [57, 303]]

------------------------------ Epoch 482 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.331049
- Iter 028 / 029, Loss: 0.426366

* Train accuracy / confusion: 84.16% / [[269, 93], [54, 512]], 
* Val   accuracy / confusion: 75.08% / [[140, 90], [57, 303]]

------------------------------ Epoch 483 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.354877
- Iter 028 / 029, Loss: 0.438725

* Train accuracy / confusion: 83.51% / [[271, 92], [61, 504]], 
* Val   accuracy / confusion: 72.88% / [[135, 95], [65, 295]]

------------------------------ Epoch 484 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.314259
- Iter 028 / 029, Loss: 0.283377

* Train accuracy / confusion: 84.38% / [[274, 85], [60, 509]], 
* Val   accuracy / confusion: 74.24% / [[141, 89], [63, 297]]

------------------------------ Epoch 485 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.253127
- Iter 028 / 029, Loss: 0.519521

* Train accuracy / confusion: 81.90% / [[265, 98], [70, 495]], 
* Val   accuracy / confusion: 71.19% / [[127, 103], [67, 293]]

------------------------------ Epoch 486 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.333658
- Iter 028 / 029, Loss: 0.275161

* Train accuracy / confusion: 82.00% / [[265, 97], [70, 496]], 
* Val   accuracy / confusion: 73.56% / [[139, 91], [65, 295]]

------------------------------ Epoch 487 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.434797
- Iter 028 / 029, Loss: 0.553604

* Train accuracy / confusion: 85.88% / [[283, 79], [52, 514]], 
* Val   accuracy / confusion: 75.08% / [[146, 84], [63, 297]]

------------------------------ Epoch 488 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.305505
- Iter 028 / 029, Loss: 0.356626

* Train accuracy / confusion: 83.08% / [[275, 83], [74, 496]], 
* Val   accuracy / confusion: 74.58% / [[146, 84], [66, 294]]

------------------------------ Epoch 489 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.248035
- Iter 028 / 029, Loss: 0.578284

* Train accuracy / confusion: 82.44% / [[266, 99], [64, 499]], 
* Val   accuracy / confusion: 73.22% / [[146, 84], [74, 286]]

------------------------------ Epoch 490 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.358779
- Iter 028 / 029, Loss: 0.498673

* Train accuracy / confusion: 81.03% / [[260, 103], [73, 492]], 
* Val   accuracy / confusion: 75.76% / [[145, 85], [58, 302]]

------------------------------ Epoch 491 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.374546
- Iter 028 / 029, Loss: 0.406871

* Train accuracy / confusion: 81.25% / [[264, 98], [76, 490]], 
* Val   accuracy / confusion: 73.90% / [[140, 90], [64, 296]]

------------------------------ Epoch 492 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.596815
- Iter 028 / 029, Loss: 0.476867

* Train accuracy / confusion: 82.00% / [[263, 100], [67, 498]], 
* Val   accuracy / confusion: 73.39% / [[136, 94], [63, 297]]

------------------------------ Epoch 493 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.317820
- Iter 028 / 029, Loss: 0.326885

* Train accuracy / confusion: 83.19% / [[267, 94], [62, 505]], 
* Val   accuracy / confusion: 73.73% / [[141, 89], [66, 294]]

------------------------------ Epoch 494 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.314305
- Iter 028 / 029, Loss: 0.354487

* Train accuracy / confusion: 83.19% / [[268, 96], [60, 504]], 
* Val   accuracy / confusion: 74.58% / [[140, 90], [60, 300]]

------------------------------ Epoch 495 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.349116
- Iter 028 / 029, Loss: 0.557052

* Train accuracy / confusion: 82.33% / [[266, 94], [70, 498]], 
* Val   accuracy / confusion: 74.58% / [[144, 86], [64, 296]]

------------------------------ Epoch 496 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.332235
- Iter 028 / 029, Loss: 0.406870

* Train accuracy / confusion: 84.16% / [[276, 86], [61, 505]], 
* Val   accuracy / confusion: 72.54% / [[134, 96], [66, 294]]

------------------------------ Epoch 497 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.180964
- Iter 028 / 029, Loss: 0.313908

* Train accuracy / confusion: 82.97% / [[267, 96], [62, 503]], 
* Val   accuracy / confusion: 74.58% / [[137, 93], [57, 303]]

------------------------------ Epoch 498 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.296993
- Iter 028 / 029, Loss: 0.334516

* Train accuracy / confusion: 82.65% / [[274, 90], [71, 493]], 
* Val   accuracy / confusion: 75.42% / [[148, 82], [63, 297]]

------------------------------ Epoch 499 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.477398
- Iter 028 / 029, Loss: 0.461907

* Train accuracy / confusion: 82.87% / [[264, 99], [60, 505]], 
* Val   accuracy / confusion: 72.37% / [[138, 92], [71, 289]]

------------------------------ Epoch 500 / 500, Learning rate: 9.56e-05 ------------------------------
- Iter 014 / 029, Loss: 0.359549
- Iter 028 / 029, Loss: 0.332107

* Train accuracy / confusion: 83.94% / [[272, 92], [57, 507]], 
* Val   accuracy / confusion: 74.41% / [[143, 87], [64, 296]]

**************************************** Training Ends ****************************************

- Test accuracy (last model): 72.00%
- Confusion matrix (last model):
 [[ 913  497]
 [ 511 1679]]

- Test accuracy (best model): 72.47%
- Confusion matrix (best model):
 [[ 934  476]
 [ 515 1675]]

# checkpoint save path
if save_checkpoint:
    os.makedirs('checkpoint/', exist_ok=True)
    today = datetime.date.today()
    torch.save(best_model_state, f'checkpoint/{today.year % 100}{today.month:02d}{today.day}_{nb_fname}_TinyCNN_best')
    torch.save(last_model_state, f'checkpoint/{today.year % 100}{today.month:02d}{today.day}_{nb_fname}_TinyCNN_last')

print('- Debug table:')
pprint.pp(last_test_debug, indent=2, width=100)

- Debug table:
{ '01183': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01303198_020317'},
  '00697': {'GT': 0, 'Acc': '  0.00%', 'Pred': [0, 30], 'edfname': '00983533_290618'},
  '00825': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01129445_130220'},
  '00504': {'GT': 0, 'Acc': '  0.00%', 'Pred': [0, 30], 'edfname': '00813343_041218'},
  '00192': {'GT': 0, 'Acc': '  0.00%', 'Pred': [0, 30], 'edfname': '00608961_131118'},
  '00134': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '00446328_171116'},
  '00741': {'GT': 0, 'Acc': ' 46.67%', 'Pred': [14, 16], 'edfname': '01025734_280715'},
  '00206': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00616193_090218'},
  '01231': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01334787_211117'},
  '00793': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01086373_020615'},
  '01045': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01235281_191015'},
  '00407': {'GT': 1, 'Acc': ' 36.67%', 'Pred': [19, 11], 'edfname': '00740694_110315'},
  '00669': {'GT': 1, 'Acc': '  0.00%', 'Pred': [30, 0], 'edfname': '00957862_230317'},
  '00843': {'GT': 1, 'Acc': '  0.00%', 'Pred': [30, 0], 'edfname': '01135545_230715'},
  '00029': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00164098_180919'},
  '00299': {'GT': 0, 'Acc': '  0.00%', 'Pred': [0, 30], 'edfname': '00671212_160819'},
  '00702': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00985987_180518'},
  '01069': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01243158_301115'},
  '00913': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01151967_160414'},
  '01307': {'GT': 0, 'Acc': '  3.33%', 'Pred': [1, 29], 'edfname': '01376302_060718'},
  '00638': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00941649_111218'},
  '00286': {'GT': 1, 'Acc': '  0.00%', 'Pred': [30, 0], 'edfname': '00663561_030414'},
  '00954': {'GT': 1, 'Acc': ' 20.00%', 'Pred': [24, 6], 'edfname': '01178797_240914'},
  '00587': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00894185_250817'},
  '00542': {'GT': 1, 'Acc': ' 76.67%', 'Pred': [7, 23], 'edfname': '00852650_170818'},
  '00996': {'GT': 1, 'Acc': ' 60.00%', 'Pred': [12, 18], 'edfname': '01204692_120315'},
  '00403': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00739162_011215'},
  '00408': {'GT': 0, 'Acc': '  3.33%', 'Pred': [1, 29], 'edfname': '00740750_110315'},
  '00078': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00324958_271118'},
  '00277': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00657017_281218'},
  '00671': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00958455_200917'},
  '01066': {'GT': 0, 'Acc': ' 86.67%', 'Pred': [26, 4], 'edfname': '01242983_071215'},
  '00965': {'GT': 1, 'Acc': ' 86.67%', 'Pred': [4, 26], 'edfname': '01186214'},
  '01125': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01276737_300616'},
  '00227': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00626957_071217'},
  '00531': {'GT': 0, 'Acc': ' 86.67%', 'Pred': [26, 4], 'edfname': '00840844_250119'},
  '00088': {'GT': 1, 'Acc': ' 50.00%', 'Pred': [15, 15], 'edfname': '00344923_021116'},
  '00267': {'GT': 1, 'Acc': ' 80.00%', 'Pred': [6, 24], 'edfname': '00650465_160318'},
  '00069': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '00307906_230617'},
  '00365': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00712852_060418'},
  '00991': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '01203444_090819'},
  '00815': {'GT': 0, 'Acc': ' 86.67%', 'Pred': [26, 4], 'edfname': '01125477_030918'},
  '01351': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01409497_111219'},
  '00065': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00293228_070918'},
  '00952': {'GT': 1, 'Acc': ' 50.00%', 'Pred': [15, 15], 'edfname': '01178672_300518'},
  '00124': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00418981_060116'},
  '00854': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01138301_230114'},
  '00472': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00784418_201016'},
  '01258': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '01348039_181017'},
  '01375': {'GT': 1, 'Acc': ' 63.33%', 'Pred': [11, 19], 'edfname': '01429374_230519'},
  '00885': {'GT': 0, 'Acc': ' 40.00%', 'Pred': [12, 18], 'edfname': '01142810_180214'},
  '00917': {'GT': 0, 'Acc': ' 13.33%', 'Pred': [4, 26], 'edfname': '01154159_230414'},
  '00938': {'GT': 0, 'Acc': '  0.00%', 'Pred': [0, 30], 'edfname': '01161826_050916'},
  '00881': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01141790_190214'},
  '00096': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00369252_131216'},
  '01075': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01250004_260116'},
  '01165': {'GT': 0, 'Acc': ' 40.00%', 'Pred': [12, 18], 'edfname': '01296533_281116'},
  '01067': {'GT': 1, 'Acc': '  0.00%', 'Pred': [30, 0], 'edfname': '01242984_211215'},
  '00828': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01131959_310118'},
  '01337': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01400560_160419'},
  '00383': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00723110_240419'},
  '00900': {'GT': 0, 'Acc': ' 26.67%', 'Pred': [8, 22], 'edfname': '01147100'},
  '01336': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '01398060_050918'},
  '01115': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01271298_270319'},
  '00667': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00956561_241116'},
  '00439': {'GT': 0, 'Acc': ' 90.00%', 'Pred': [27, 3], 'edfname': '00760780_141118'},
  '00369': {'GT': 1, 'Acc': ' 10.00%', 'Pred': [27, 3], 'edfname': '00715828_111016'},
  '00955': {'GT': 1, 'Acc': ' 73.33%', 'Pred': [8, 22], 'edfname': '01178888_161117'},
  '00300': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00671379_290617'},
  '01196': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01307883_100217'},
  '00923': {'GT': 0, 'Acc': ' 63.33%', 'Pred': [19, 11], 'edfname': '01155730_070514'},
  '00058': {'GT': 0, 'Acc': ' 20.00%', 'Pred': [6, 24], 'edfname': '00285244_020414'},
  '00584': {'GT': 1, 'Acc': ' 16.67%', 'Pred': [25, 5], 'edfname': '00891889_060717'},
  '00749': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01027623_260916'},
  '01334': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01396872_021018'},
  '00588': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00895530_090616'},
  '00679': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00963069_150618'},
  '00385': {'GT': 0, 'Acc': '  0.00%', 'Pred': [0, 30], 'edfname': '00723232_270318'},
  '00018': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00128526_180817'},
  '01281': {'GT': 1, 'Acc': ' 70.00%', 'Pred': [9, 21], 'edfname': '01358607_280918'},
  '00651': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00951808_251116'},
  '01253': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01344212_240817'},
  '01035': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01231654_260417'},
  '00551': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '00865039_170816'},
  '00870': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01139947_120214'},
  '00578': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '00888613_080618'},
  '00730': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01011922_270815'},
  '00516': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00823206_130514'},
  '01330': {'GT': 0, 'Acc': ' 90.00%', 'Pred': [27, 3], 'edfname': '01392885_240718'},
  '00944': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01168853_070316'},
  '00125': {'GT': 0, 'Acc': ' 76.67%', 'Pred': [23, 7], 'edfname': '00418981_090316'},
  '00508': {'GT': 0, 'Acc': ' 93.33%', 'Pred': [28, 2], 'edfname': '00817022_010415'},
  '01317': {'GT': 1, 'Acc': ' 73.33%', 'Pred': [8, 22], 'edfname': '01381606_160518'},
  '00608': {'GT': 1, 'Acc': '  0.00%', 'Pred': [30, 0], 'edfname': '00907971_030217'},
  '00471': {'GT': 1, 'Acc': ' 76.67%', 'Pred': [7, 23], 'edfname': '00784417_100315'},
  '00821': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01128393_300715'},
  '00122': {'GT': 0, 'Acc': ' 90.00%', 'Pred': [27, 3], 'edfname': '00416942_190516'},
  '01007': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01211467_070415'},
  '01247': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01339759_310717'},
  '00173': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00601028_290618'},
  '01026': {'GT': 0, 'Acc': ' 86.67%', 'Pred': [26, 4], 'edfname': '01225123_050815'},
  '01018': {'GT': 1, 'Acc': '  0.00%', 'Pred': [30, 0], 'edfname': '01216443_240518'},
  '00418': {'GT': 1, 'Acc': ' 90.00%', 'Pred': [3, 27], 'edfname': '00745209_220916'},
  '01206': {'GT': 1, 'Acc': '  3.33%', 'Pred': [29, 1], 'edfname': '01314786_200317'},
  '01215': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01321744_130417'},
  '01105': {'GT': 0, 'Acc': ' 50.00%', 'Pred': [15, 15], 'edfname': '01266696_110516'},
  '00598': {'GT': 1, 'Acc': ' 70.00%', 'Pred': [9, 21], 'edfname': '00899964_110414'},
  '00851': {'GT': 0, 'Acc': ' 10.00%', 'Pred': [3, 27], 'edfname': '01138297_230114'},
  '01138': {'GT': 0, 'Acc': ' 53.33%', 'Pred': [16, 14], 'edfname': '01281605_070716'},
  '00079': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00325929_170119'},
  '00245': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00637371_050917'},
  '00591': {'GT': 0, 'Acc': ' 63.33%', 'Pred': [19, 11], 'edfname': '00896386_240914'},
  '00329': {'GT': 0, 'Acc': ' 83.33%', 'Pred': [25, 5], 'edfname': '00685248_150414'},
  '00272': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00651389_281016'},
  '00176': {'GT': 0, 'Acc': ' 56.67%', 'Pred': [17, 13], 'edfname': '00602435_270217'},
  '00807': {'GT': 1, 'Acc': ' 13.33%', 'Pred': [26, 4], 'edfname': '01112291_231115'},
  '00271': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00651252_140618'},
  '00712': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00988278_210915'},
  '00974': {'GT': 1, 'Acc': ' 36.67%', 'Pred': [19, 11], 'edfname': '01193508_171214'},
  '01163': {'GT': 1, 'Acc': '  0.00%', 'Pred': [30, 0], 'edfname': '01296342_141116'}}

1D CNN: M5-like model

class M5(nn.Module):
    def __init__(self, n_input=20, n_output=3, stride=4, n_channel=256, 
                 use_age=True, final_pool='average'):
        super().__init__()
        
        if final_pool not in {'average', 'max'}:
            raise ValueError("final_pool must be set to one of ['average', 'max']")
        
        self.use_age = use_age
        
        self.conv1 = nn.Conv1d(n_input, n_channel, kernel_size=41, stride=2)
        self.bn1 = nn.BatchNorm1d(n_channel)
        self.pool1 = nn.MaxPool1d(2)
        
        self.conv2 = nn.Conv1d(n_channel, n_channel, kernel_size=11)
        self.bn2 = nn.BatchNorm1d(n_channel)
        self.pool2 = nn.MaxPool1d(2)
        
        self.conv3 = nn.Conv1d(n_channel, 2 * n_channel, kernel_size=11)
        self.bn3 = nn.BatchNorm1d(2 * n_channel)
        self.pool3 = nn.MaxPool1d(2)
        
        self.conv4 = nn.Conv1d(2 * n_channel, 2 * n_channel, kernel_size=11)
        self.bn4 = nn.BatchNorm1d(2 * n_channel)
        self.pool4 = nn.MaxPool1d(2)
        
        self.conv5 = nn.Conv1d(2 * n_channel, 2 * n_channel, kernel_size=11)
        self.bn5 = nn.BatchNorm1d(2 * n_channel)
        self.pool5 = nn.MaxPool1d(2)
        
        if final_pool == 'average':
            self.final_pool = nn.AdaptiveAvgPool1d(1)
        elif final_pool == 'max':
            self.final_pool = nn.AdaptiveMaxPool1d(1)
    
        if self.use_age:        
            self.fc1 = nn.Linear(2 * n_channel + 1, 2 * n_channel)
        else:
            self.fc1 = nn.Linear(2 * n_channel, 2 * n_channel)
            
        self.dropout = nn.Dropout(p=0.3)
        self.bnfc1 = nn.BatchNorm1d(2 * n_channel)
        self.fc2 = nn.Linear(2 * n_channel, n_output)
        
    def reset_weights(self):
        for m in self.modules():
            if hasattr(m, 'reset_parameters'):
                m.reset_parameters()

    def forward(self, x, age, print_shape=False):
        # conv-bn-relu-pool 
        x = self.conv1(x)
        x = F.relu(self.bn1(x))
        x = self.pool1(x)

        x = self.conv2(x)
        x = F.relu(self.bn2(x))
        x = self.pool2(x)

        x = self.conv3(x)
        x = F.relu(self.bn3(x))
        x = self.pool3(x)

        x = self.conv4(x)
        x = F.relu(self.bn4(x))
        x = self.pool4(x)

        x = self.conv5(x)
        x = F.relu(self.bn5(x))
        x = self.pool5(x)

        if print_shape:
            print('Shape right before squeezing:', x.shape)
    
        x = self.final_pool(x).squeeze()
        if self.use_age:
            x = torch.cat((x, age.reshape(-1, 1)), dim=1)

        # fc-bn-dropout-relu-fc
        x = self.fc1(x)
        x = self.bnfc1(x)
        x = self.dropout(x)
        x = F.relu(x)
        x = self.fc2(x)
        
        return x
        # return F.log_softmax(x, dim=1)

model = M5(n_input=train_dataset[0]['signal'].shape[0], 
           n_output=2, 
           use_age=True, 
           final_pool='max')

model = model.to(device, dtype=torch.float32)
print(model)
print()

# tensorboard visualization
visualize_network_tensorboard(model, 'M5-like')

# number of parameters
n = count_parameters(model)
print(f'The Number of parameters of the model: {n:,}')

M5(
  (conv1): Conv1d(20, 256, kernel_size=(41,), stride=(2,))
  (bn1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (pool1): MaxPool1d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
  (conv2): Conv1d(256, 256, kernel_size=(11,), stride=(1,))
  (bn2): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (pool2): MaxPool1d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
  (conv3): Conv1d(256, 512, kernel_size=(11,), stride=(1,))
  (bn3): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (pool3): MaxPool1d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
  (conv4): Conv1d(512, 512, kernel_size=(11,), stride=(1,))
  (bn4): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (pool4): MaxPool1d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
  (conv5): Conv1d(512, 512, kernel_size=(11,), stride=(1,))
  (bn5): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (pool5): MaxPool1d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
  (final_pool): AdaptiveMaxPool1d(output_size=1)
  (fc1): Linear(in_features=513, out_features=512, bias=True)
  (dropout): Dropout(p=0.3, inplace=False)
  (bnfc1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (fc2): Linear(in_features=512, out_features=2, bias=True)
)

Shape right before squeezing: torch.Size([32, 512, 21])
The Number of parameters of the model: 8,411,138

record = learning_rate_search(model, 
                              min_log_lr=-4.5, 
                              max_log_lr=-1.4, 
                              trials=300, 
                              epochs=1)
draw_learning_rate_record(record)
best_log_lr = record[np.argmax(np.array([v for lr, v in record]))][0]

# best_log_lr = -3.5
print('best_log_lr:', best_log_lr)

best_log_lr: -2.7162397010443335

# reduce the learning after [lr_schedule_step] epochs by a factor of 10
n_epoch = 500
lr_schedule_step = 200
log_interval = len(train_loader) // 2

loss_history = []
train_acc_history = []
val_acc_history = []
best_val_acc = 0

model.reset_weights()
optimizer = optim.AdamW(model.parameters(), lr=10 ** best_log_lr, weight_decay=0.0001)
scheduler = optim.lr_scheduler.StepLR(optimizer, step_size=lr_schedule_step, gamma=0.1)

print(f'{"*"*40} Training Starts {"*"*40}')

for epoch in tqdm(range(1, n_epoch + 1)):
    print(f'{"-"*30} Epoch {epoch:03d} / {n_epoch:03d}, Learning rate: {optimizer.param_groups[-1]["lr"]:.2e} {"-"*30}')
    
    # train
    loss, train_accuracy, train_confusion = train_one_epoch(model, optimizer, log_interval)
    loss_history.extend(loss)
    train_acc_history.append(train_accuracy)
    
    # validation
    val_accuracy, val_confusion = check_val_accuracy(model, repeat=5)
    val_acc_history.append(val_accuracy)
    
    if best_val_acc < val_accuracy:
        best_val_acc = val_accuracy
        best_model_state = deepcopy(model.state_dict())
    
    # learning rate schedule
    scheduler.step()
    
    print()
    print(f'* Train accuracy / confusion: {train_accuracy:.2f}% / {train_confusion.tolist()}, ')
    print(f'* Val   accuracy / confusion: {val_accuracy:.2f}% / {val_confusion.tolist()}')
    print()

print(f'{"*"*40} Training Ends {"*"*40}')

# draw the training loss plot
draw_loss_plot(loss_history)
draw_accuracy_history(train_acc_history, val_acc_history)
    
# test the last model
last_model_state = deepcopy(model.state_dict())
last_test_accuracy, last_test_confusion, last_test_debug = check_test_accuracy(model, repeat=30)

print(f'- Test accuracy (last model): {last_test_accuracy:.2f}%')
print('- Confusion matrix (last model):\n', last_test_confusion)
print()

draw_confusion(last_test_confusion)

# test the best model
model.load_state_dict(best_model_state)
best_test_accuracy, best_test_confusion, best_test_debug = check_test_accuracy(model, repeat=30)

print(f'- Test accuracy (best model): {best_test_accuracy:.2f}%')
print('- Confusion matrix (best model):\n', best_test_confusion)
print()

draw_confusion(best_test_confusion)

**************************************** Training Starts ****************************************

------------------------------ Epoch 001 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.685462
- Iter 028 / 029, Loss: 0.678188

* Train accuracy / confusion: 58.51% / [[131, 232], [153, 412]], 
* Val   accuracy / confusion: 55.08% / [[123, 107], [158, 202]]

------------------------------ Epoch 002 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.687887
- Iter 028 / 029, Loss: 0.731904

* Train accuracy / confusion: 59.59% / [[107, 257], [118, 446]], 
* Val   accuracy / confusion: 61.02% / [[79, 151], [79, 281]]

------------------------------ Epoch 003 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.810514
- Iter 028 / 029, Loss: 0.706069

* Train accuracy / confusion: 61.85% / [[103, 261], [93, 471]], 
* Val   accuracy / confusion: 63.22% / [[33, 197], [20, 340]]

------------------------------ Epoch 004 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.703000
- Iter 028 / 029, Loss: 0.671123

* Train accuracy / confusion: 62.93% / [[125, 241], [103, 459]], 
* Val   accuracy / confusion: 61.53% / [[3, 227], [0, 360]]

------------------------------ Epoch 005 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.602015
- Iter 028 / 029, Loss: 0.555473

* Train accuracy / confusion: 66.92% / [[140, 222], [85, 481]], 
* Val   accuracy / confusion: 63.56% / [[20, 210], [5, 355]]

------------------------------ Epoch 006 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.740283
- Iter 028 / 029, Loss: 0.740140

* Train accuracy / confusion: 65.62% / [[148, 214], [105, 461]], 
* Val   accuracy / confusion: 64.58% / [[138, 92], [117, 243]]

------------------------------ Epoch 007 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.587951
- Iter 028 / 029, Loss: 0.714952

* Train accuracy / confusion: 66.81% / [[140, 223], [85, 480]], 
* Val   accuracy / confusion: 60.85% / [[127, 103], [128, 232]]

------------------------------ Epoch 008 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.648321
- Iter 028 / 029, Loss: 0.622020

* Train accuracy / confusion: 67.46% / [[190, 172], [130, 436]], 
* Val   accuracy / confusion: 69.15% / [[71, 159], [23, 337]]

------------------------------ Epoch 009 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.736374
- Iter 028 / 029, Loss: 0.680417

* Train accuracy / confusion: 67.67% / [[182, 181], [119, 446]], 
* Val   accuracy / confusion: 73.39% / [[105, 125], [32, 328]]

------------------------------ Epoch 010 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.562127
- Iter 028 / 029, Loss: 0.434048

* Train accuracy / confusion: 70.58% / [[189, 170], [103, 466]], 
* Val   accuracy / confusion: 67.97% / [[42, 188], [1, 359]]

------------------------------ Epoch 011 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.412661
- Iter 028 / 029, Loss: 0.605394

* Train accuracy / confusion: 71.12% / [[191, 172], [96, 469]], 
* Val   accuracy / confusion: 73.73% / [[168, 62], [93, 267]]

------------------------------ Epoch 012 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.465382
- Iter 028 / 029, Loss: 0.637009

* Train accuracy / confusion: 70.91% / [[196, 166], [104, 462]], 
* Val   accuracy / confusion: 73.05% / [[116, 114], [45, 315]]

------------------------------ Epoch 013 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.634341
- Iter 028 / 029, Loss: 0.600267

* Train accuracy / confusion: 71.55% / [[212, 152], [112, 452]], 
* Val   accuracy / confusion: 71.19% / [[117, 113], [57, 303]]

------------------------------ Epoch 014 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.514843
- Iter 028 / 029, Loss: 0.607926

* Train accuracy / confusion: 66.92% / [[198, 168], [139, 423]], 
* Val   accuracy / confusion: 67.63% / [[48, 182], [9, 351]]

------------------------------ Epoch 015 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.623806
- Iter 028 / 029, Loss: 0.505645

* Train accuracy / confusion: 69.07% / [[185, 174], [113, 456]], 
* Val   accuracy / confusion: 68.31% / [[141, 89], [98, 262]]

------------------------------ Epoch 016 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.554377
- Iter 028 / 029, Loss: 0.416510

* Train accuracy / confusion: 71.12% / [[198, 163], [105, 462]], 
* Val   accuracy / confusion: 71.19% / [[164, 66], [104, 256]]

------------------------------ Epoch 017 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.614937
- Iter 028 / 029, Loss: 0.584349

* Train accuracy / confusion: 70.47% / [[216, 146], [128, 438]], 
* Val   accuracy / confusion: 74.24% / [[125, 105], [47, 313]]

------------------------------ Epoch 018 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.476456
- Iter 028 / 029, Loss: 0.579067

* Train accuracy / confusion: 71.01% / [[196, 167], [102, 463]], 
* Val   accuracy / confusion: 75.42% / [[134, 96], [49, 311]]

------------------------------ Epoch 019 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.700761
- Iter 028 / 029, Loss: 0.607177

* Train accuracy / confusion: 69.94% / [[206, 159], [120, 443]], 
* Val   accuracy / confusion: 72.20% / [[107, 123], [41, 319]]

------------------------------ Epoch 020 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.558230
- Iter 028 / 029, Loss: 0.622491

* Train accuracy / confusion: 70.15% / [[187, 174], [103, 464]], 
* Val   accuracy / confusion: 71.19% / [[118, 112], [58, 302]]

------------------------------ Epoch 021 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.566658
- Iter 028 / 029, Loss: 0.538258

* Train accuracy / confusion: 70.47% / [[185, 172], [102, 469]], 
* Val   accuracy / confusion: 73.39% / [[136, 94], [63, 297]]

------------------------------ Epoch 022 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.533460
- Iter 028 / 029, Loss: 0.590511

* Train accuracy / confusion: 70.26% / [[198, 165], [111, 454]], 
* Val   accuracy / confusion: 76.10% / [[116, 114], [27, 333]]

------------------------------ Epoch 023 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.760657
- Iter 028 / 029, Loss: 0.555490

* Train accuracy / confusion: 71.88% / [[199, 161], [100, 468]], 
* Val   accuracy / confusion: 74.58% / [[153, 77], [73, 287]]

------------------------------ Epoch 024 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.566048
- Iter 028 / 029, Loss: 0.634326

* Train accuracy / confusion: 72.09% / [[212, 150], [109, 457]], 
* Val   accuracy / confusion: 73.05% / [[80, 150], [9, 351]]

------------------------------ Epoch 025 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.704135
- Iter 028 / 029, Loss: 0.709714

* Train accuracy / confusion: 70.37% / [[198, 166], [109, 455]], 
* Val   accuracy / confusion: 76.61% / [[144, 86], [52, 308]]

------------------------------ Epoch 026 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.505385
- Iter 028 / 029, Loss: 0.500971

* Train accuracy / confusion: 72.84% / [[208, 152], [100, 468]], 
* Val   accuracy / confusion: 73.73% / [[120, 110], [45, 315]]

------------------------------ Epoch 027 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.472758
- Iter 028 / 029, Loss: 0.533128

* Train accuracy / confusion: 72.31% / [[210, 153], [104, 461]], 
* Val   accuracy / confusion: 74.24% / [[161, 69], [83, 277]]

------------------------------ Epoch 028 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.540233
- Iter 028 / 029, Loss: 0.604961

* Train accuracy / confusion: 75.43% / [[232, 130], [98, 468]], 
* Val   accuracy / confusion: 74.58% / [[144, 86], [64, 296]]

------------------------------ Epoch 029 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.637030
- Iter 028 / 029, Loss: 0.509313

* Train accuracy / confusion: 72.52% / [[198, 166], [89, 475]], 
* Val   accuracy / confusion: 72.20% / [[100, 130], [34, 326]]

------------------------------ Epoch 030 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.577554
- Iter 028 / 029, Loss: 0.764266

* Train accuracy / confusion: 70.58% / [[188, 172], [101, 467]], 
* Val   accuracy / confusion: 72.54% / [[84, 146], [16, 344]]

------------------------------ Epoch 031 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.735710
- Iter 028 / 029, Loss: 0.620574

* Train accuracy / confusion: 73.60% / [[219, 144], [101, 464]], 
* Val   accuracy / confusion: 71.86% / [[84, 146], [20, 340]]

------------------------------ Epoch 032 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.401889
- Iter 028 / 029, Loss: 0.526930

* Train accuracy / confusion: 73.38% / [[210, 151], [96, 471]], 
* Val   accuracy / confusion: 72.71% / [[155, 75], [86, 274]]

------------------------------ Epoch 033 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.385711
- Iter 028 / 029, Loss: 0.482243

* Train accuracy / confusion: 73.60% / [[215, 140], [105, 468]], 
* Val   accuracy / confusion: 73.90% / [[128, 102], [52, 308]]

------------------------------ Epoch 034 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.647362
- Iter 028 / 029, Loss: 0.479482

* Train accuracy / confusion: 73.81% / [[210, 148], [95, 475]], 
* Val   accuracy / confusion: 68.31% / [[184, 46], [141, 219]]

------------------------------ Epoch 035 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.550135
- Iter 028 / 029, Loss: 0.455041

* Train accuracy / confusion: 74.25% / [[216, 145], [94, 473]], 
* Val   accuracy / confusion: 72.54% / [[87, 143], [19, 341]]

------------------------------ Epoch 036 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.603955
- Iter 028 / 029, Loss: 0.591803

* Train accuracy / confusion: 74.03% / [[233, 131], [110, 454]], 
* Val   accuracy / confusion: 76.44% / [[121, 109], [30, 330]]

------------------------------ Epoch 037 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.511180
- Iter 028 / 029, Loss: 0.499753

* Train accuracy / confusion: 74.14% / [[218, 145], [95, 470]], 
* Val   accuracy / confusion: 70.00% / [[188, 42], [135, 225]]

------------------------------ Epoch 038 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.489841
- Iter 028 / 029, Loss: 0.480828

* Train accuracy / confusion: 74.46% / [[220, 141], [96, 471]], 
* Val   accuracy / confusion: 66.95% / [[38, 192], [3, 357]]

------------------------------ Epoch 039 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.420153
- Iter 028 / 029, Loss: 0.421544

* Train accuracy / confusion: 74.14% / [[227, 139], [101, 461]], 
* Val   accuracy / confusion: 72.20% / [[170, 60], [104, 256]]

------------------------------ Epoch 040 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.451115
- Iter 028 / 029, Loss: 0.537000

* Train accuracy / confusion: 74.25% / [[226, 136], [103, 463]], 
* Val   accuracy / confusion: 75.08% / [[119, 111], [36, 324]]

------------------------------ Epoch 041 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.532969
- Iter 028 / 029, Loss: 0.473312

* Train accuracy / confusion: 74.57% / [[215, 148], [88, 477]], 
* Val   accuracy / confusion: 73.05% / [[101, 129], [30, 330]]

------------------------------ Epoch 042 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.485807
- Iter 028 / 029, Loss: 0.631229

* Train accuracy / confusion: 72.95% / [[217, 143], [108, 460]], 
* Val   accuracy / confusion: 73.22% / [[87, 143], [15, 345]]

------------------------------ Epoch 043 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.609160
- Iter 028 / 029, Loss: 0.609701

* Train accuracy / confusion: 74.14% / [[219, 142], [98, 469]], 
* Val   accuracy / confusion: 76.10% / [[161, 69], [72, 288]]

------------------------------ Epoch 044 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.458777
- Iter 028 / 029, Loss: 0.604419

* Train accuracy / confusion: 73.81% / [[220, 140], [103, 465]], 
* Val   accuracy / confusion: 75.25% / [[153, 77], [69, 291]]

------------------------------ Epoch 045 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.430115
- Iter 028 / 029, Loss: 0.498915

* Train accuracy / confusion: 74.03% / [[211, 151], [90, 476]], 
* Val   accuracy / confusion: 71.19% / [[85, 145], [25, 335]]

------------------------------ Epoch 046 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.464470
- Iter 028 / 029, Loss: 0.461482

* Train accuracy / confusion: 75.11% / [[222, 141], [90, 475]], 
* Val   accuracy / confusion: 72.03% / [[157, 73], [92, 268]]

------------------------------ Epoch 047 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.586823
- Iter 028 / 029, Loss: 0.516701

* Train accuracy / confusion: 74.68% / [[217, 145], [90, 476]], 
* Val   accuracy / confusion: 72.54% / [[163, 67], [95, 265]]

------------------------------ Epoch 048 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.467314
- Iter 028 / 029, Loss: 0.400910

* Train accuracy / confusion: 74.57% / [[219, 143], [93, 473]], 
* Val   accuracy / confusion: 74.75% / [[136, 94], [55, 305]]

------------------------------ Epoch 049 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.455569
- Iter 028 / 029, Loss: 0.593278

* Train accuracy / confusion: 75.97% / [[226, 135], [88, 479]], 
* Val   accuracy / confusion: 62.20% / [[198, 32], [191, 169]]

------------------------------ Epoch 050 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.541898
- Iter 028 / 029, Loss: 0.519106

* Train accuracy / confusion: 76.94% / [[233, 130], [84, 481]], 
* Val   accuracy / confusion: 74.75% / [[137, 93], [56, 304]]

------------------------------ Epoch 051 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.461812
- Iter 028 / 029, Loss: 0.561162

* Train accuracy / confusion: 73.60% / [[209, 153], [92, 474]], 
* Val   accuracy / confusion: 74.75% / [[109, 121], [28, 332]]

------------------------------ Epoch 052 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.686395
- Iter 028 / 029, Loss: 0.675046

* Train accuracy / confusion: 74.35% / [[219, 141], [97, 471]], 
* Val   accuracy / confusion: 73.90% / [[111, 119], [35, 325]]

------------------------------ Epoch 053 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.682407
- Iter 028 / 029, Loss: 0.408368

* Train accuracy / confusion: 75.97% / [[235, 129], [94, 470]], 
* Val   accuracy / confusion: 71.53% / [[72, 158], [10, 350]]

------------------------------ Epoch 054 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.492123
- Iter 028 / 029, Loss: 0.542685

* Train accuracy / confusion: 76.08% / [[226, 137], [85, 480]], 
* Val   accuracy / confusion: 68.81% / [[177, 53], [131, 229]]

------------------------------ Epoch 055 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.568456
- Iter 028 / 029, Loss: 0.465527

* Train accuracy / confusion: 74.35% / [[207, 155], [83, 483]], 
* Val   accuracy / confusion: 71.53% / [[168, 62], [106, 254]]

------------------------------ Epoch 056 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.522690
- Iter 028 / 029, Loss: 0.483667

* Train accuracy / confusion: 75.00% / [[223, 135], [97, 473]], 
* Val   accuracy / confusion: 72.88% / [[161, 69], [91, 269]]

------------------------------ Epoch 057 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.475738
- Iter 028 / 029, Loss: 0.621266

* Train accuracy / confusion: 74.14% / [[208, 157], [83, 480]], 
* Val   accuracy / confusion: 73.73% / [[151, 79], [76, 284]]

------------------------------ Epoch 058 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.761177
- Iter 028 / 029, Loss: 0.646525

* Train accuracy / confusion: 75.00% / [[234, 129], [103, 462]], 
* Val   accuracy / confusion: 74.07% / [[132, 98], [55, 305]]

------------------------------ Epoch 059 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.385408
- Iter 028 / 029, Loss: 0.616260

* Train accuracy / confusion: 75.65% / [[229, 129], [97, 473]], 
* Val   accuracy / confusion: 72.03% / [[95, 135], [30, 330]]

------------------------------ Epoch 060 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.497723
- Iter 028 / 029, Loss: 0.332670

* Train accuracy / confusion: 76.29% / [[223, 135], [85, 485]], 
* Val   accuracy / confusion: 74.24% / [[116, 114], [38, 322]]

------------------------------ Epoch 061 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.463461
- Iter 028 / 029, Loss: 0.544525

* Train accuracy / confusion: 76.19% / [[223, 140], [81, 484]], 
* Val   accuracy / confusion: 76.10% / [[151, 79], [62, 298]]

------------------------------ Epoch 062 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.410450
- Iter 028 / 029, Loss: 0.458128

* Train accuracy / confusion: 74.14% / [[212, 151], [89, 476]], 
* Val   accuracy / confusion: 75.08% / [[109, 121], [26, 334]]

------------------------------ Epoch 063 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.557521
- Iter 028 / 029, Loss: 0.596670

* Train accuracy / confusion: 74.35% / [[217, 145], [93, 473]], 
* Val   accuracy / confusion: 77.12% / [[136, 94], [41, 319]]

------------------------------ Epoch 064 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.444364
- Iter 028 / 029, Loss: 0.359691

* Train accuracy / confusion: 75.54% / [[218, 142], [85, 483]], 
* Val   accuracy / confusion: 74.07% / [[165, 65], [88, 272]]

------------------------------ Epoch 065 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.604953
- Iter 028 / 029, Loss: 0.472783

* Train accuracy / confusion: 76.62% / [[225, 137], [80, 486]], 
* Val   accuracy / confusion: 74.58% / [[118, 112], [38, 322]]

------------------------------ Epoch 066 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.462388
- Iter 028 / 029, Loss: 0.558146

* Train accuracy / confusion: 76.08% / [[232, 132], [90, 474]], 
* Val   accuracy / confusion: 76.27% / [[133, 97], [43, 317]]

------------------------------ Epoch 067 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.466160
- Iter 028 / 029, Loss: 0.568735

* Train accuracy / confusion: 75.86% / [[221, 138], [86, 483]], 
* Val   accuracy / confusion: 73.73% / [[125, 105], [50, 310]]

------------------------------ Epoch 068 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.553492
- Iter 028 / 029, Loss: 0.526521

* Train accuracy / confusion: 75.75% / [[224, 140], [85, 479]], 
* Val   accuracy / confusion: 72.54% / [[131, 99], [63, 297]]

------------------------------ Epoch 069 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.380616
- Iter 028 / 029, Loss: 0.568141

* Train accuracy / confusion: 75.54% / [[227, 135], [92, 474]], 
* Val   accuracy / confusion: 75.59% / [[156, 74], [70, 290]]

------------------------------ Epoch 070 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.484084
- Iter 028 / 029, Loss: 0.447260

* Train accuracy / confusion: 77.16% / [[230, 132], [80, 486]], 
* Val   accuracy / confusion: 74.92% / [[155, 75], [73, 287]]

------------------------------ Epoch 071 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.439582
- Iter 028 / 029, Loss: 0.495455

* Train accuracy / confusion: 75.65% / [[225, 138], [88, 477]], 
* Val   accuracy / confusion: 73.39% / [[147, 83], [74, 286]]

------------------------------ Epoch 072 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.454334
- Iter 028 / 029, Loss: 0.526294

* Train accuracy / confusion: 76.62% / [[222, 142], [75, 489]], 
* Val   accuracy / confusion: 75.08% / [[101, 129], [18, 342]]

------------------------------ Epoch 073 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.451261
- Iter 028 / 029, Loss: 0.407618

* Train accuracy / confusion: 76.83% / [[233, 127], [88, 480]], 
* Val   accuracy / confusion: 75.76% / [[125, 105], [38, 322]]

------------------------------ Epoch 074 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.375085
- Iter 028 / 029, Loss: 0.422529

* Train accuracy / confusion: 75.86% / [[218, 146], [78, 486]], 
* Val   accuracy / confusion: 69.15% / [[179, 51], [131, 229]]

------------------------------ Epoch 075 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.586300
- Iter 028 / 029, Loss: 0.488016

* Train accuracy / confusion: 76.62% / [[243, 121], [96, 468]], 
* Val   accuracy / confusion: 75.76% / [[112, 118], [25, 335]]

------------------------------ Epoch 076 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.531547
- Iter 028 / 029, Loss: 0.608338

* Train accuracy / confusion: 76.94% / [[232, 133], [81, 482]], 
* Val   accuracy / confusion: 73.56% / [[155, 75], [81, 279]]

------------------------------ Epoch 077 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.441162
- Iter 028 / 029, Loss: 0.459905

* Train accuracy / confusion: 76.19% / [[233, 129], [92, 474]], 
* Val   accuracy / confusion: 72.71% / [[102, 128], [33, 327]]

------------------------------ Epoch 078 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.635758
- Iter 028 / 029, Loss: 0.464953

* Train accuracy / confusion: 76.72% / [[232, 133], [83, 480]], 
* Val   accuracy / confusion: 73.05% / [[161, 69], [90, 270]]

------------------------------ Epoch 079 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.595157
- Iter 028 / 029, Loss: 0.532015

* Train accuracy / confusion: 75.86% / [[233, 132], [92, 471]], 
* Val   accuracy / confusion: 75.25% / [[129, 101], [45, 315]]

------------------------------ Epoch 080 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.423463
- Iter 028 / 029, Loss: 0.425904

* Train accuracy / confusion: 76.08% / [[218, 144], [78, 488]], 
* Val   accuracy / confusion: 75.08% / [[134, 96], [51, 309]]

------------------------------ Epoch 081 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.361284
- Iter 028 / 029, Loss: 0.515291

* Train accuracy / confusion: 76.72% / [[237, 123], [93, 475]], 
* Val   accuracy / confusion: 74.41% / [[145, 85], [66, 294]]

------------------------------ Epoch 082 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.541505
- Iter 028 / 029, Loss: 0.488222

* Train accuracy / confusion: 75.65% / [[232, 132], [94, 470]], 
* Val   accuracy / confusion: 70.85% / [[175, 55], [117, 243]]

------------------------------ Epoch 083 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.583653
- Iter 028 / 029, Loss: 0.467007

* Train accuracy / confusion: 75.75% / [[242, 119], [106, 461]], 
* Val   accuracy / confusion: 75.08% / [[112, 118], [29, 331]]

------------------------------ Epoch 084 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.487074
- Iter 028 / 029, Loss: 0.503133

* Train accuracy / confusion: 76.08% / [[232, 132], [90, 474]], 
* Val   accuracy / confusion: 72.37% / [[83, 147], [16, 344]]

------------------------------ Epoch 085 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.429332
- Iter 028 / 029, Loss: 0.477314

* Train accuracy / confusion: 76.29% / [[222, 138], [82, 486]], 
* Val   accuracy / confusion: 76.10% / [[137, 93], [48, 312]]

------------------------------ Epoch 086 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.470304
- Iter 028 / 029, Loss: 0.476995

* Train accuracy / confusion: 75.75% / [[228, 136], [89, 475]], 
* Val   accuracy / confusion: 74.75% / [[137, 93], [56, 304]]

------------------------------ Epoch 087 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.579012
- Iter 028 / 029, Loss: 0.578450

* Train accuracy / confusion: 77.16% / [[235, 128], [84, 481]], 
* Val   accuracy / confusion: 76.95% / [[151, 79], [57, 303]]

------------------------------ Epoch 088 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.558710
- Iter 028 / 029, Loss: 0.391678

* Train accuracy / confusion: 76.51% / [[235, 127], [91, 475]], 
* Val   accuracy / confusion: 72.37% / [[167, 63], [100, 260]]

------------------------------ Epoch 089 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.622175
- Iter 028 / 029, Loss: 0.600782

* Train accuracy / confusion: 77.16% / [[236, 125], [87, 480]], 
* Val   accuracy / confusion: 74.58% / [[119, 111], [39, 321]]

------------------------------ Epoch 090 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.672663
- Iter 028 / 029, Loss: 0.442640

* Train accuracy / confusion: 77.59% / [[232, 127], [81, 488]], 
* Val   accuracy / confusion: 73.39% / [[121, 109], [48, 312]]

------------------------------ Epoch 091 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.482572
- Iter 028 / 029, Loss: 0.512450

* Train accuracy / confusion: 75.86% / [[241, 120], [104, 463]], 
* Val   accuracy / confusion: 74.24% / [[108, 122], [30, 330]]

------------------------------ Epoch 092 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.488269
- Iter 028 / 029, Loss: 0.463167

* Train accuracy / confusion: 76.29% / [[225, 136], [84, 483]], 
* Val   accuracy / confusion: 73.90% / [[135, 95], [59, 301]]

------------------------------ Epoch 093 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.577154
- Iter 028 / 029, Loss: 0.671266

* Train accuracy / confusion: 74.57% / [[219, 143], [93, 473]], 
* Val   accuracy / confusion: 75.42% / [[126, 104], [41, 319]]

------------------------------ Epoch 094 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.427585
- Iter 028 / 029, Loss: 0.553115

* Train accuracy / confusion: 77.59% / [[230, 132], [76, 490]], 
* Val   accuracy / confusion: 75.93% / [[130, 100], [42, 318]]

------------------------------ Epoch 095 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.332805
- Iter 028 / 029, Loss: 0.521802

* Train accuracy / confusion: 77.69% / [[242, 120], [87, 479]], 
* Val   accuracy / confusion: 68.98% / [[183, 47], [136, 224]]

------------------------------ Epoch 096 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.457146
- Iter 028 / 029, Loss: 0.611440

* Train accuracy / confusion: 75.97% / [[222, 140], [83, 483]], 
* Val   accuracy / confusion: 71.69% / [[83, 147], [20, 340]]

------------------------------ Epoch 097 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.565841
- Iter 028 / 029, Loss: 0.471492

* Train accuracy / confusion: 78.34% / [[246, 119], [82, 481]], 
* Val   accuracy / confusion: 73.22% / [[169, 61], [97, 263]]

------------------------------ Epoch 098 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.502653
- Iter 028 / 029, Loss: 0.505740

* Train accuracy / confusion: 77.69% / [[226, 133], [74, 495]], 
* Val   accuracy / confusion: 74.07% / [[137, 93], [60, 300]]

------------------------------ Epoch 099 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.680466
- Iter 028 / 029, Loss: 0.410744

* Train accuracy / confusion: 76.72% / [[246, 118], [98, 466]], 
* Val   accuracy / confusion: 71.19% / [[170, 60], [110, 250]]

------------------------------ Epoch 100 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.494486
- Iter 028 / 029, Loss: 0.763107

* Train accuracy / confusion: 76.72% / [[226, 137], [79, 486]], 
* Val   accuracy / confusion: 70.51% / [[109, 121], [53, 307]]

------------------------------ Epoch 101 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.582751
- Iter 028 / 029, Loss: 0.505413

* Train accuracy / confusion: 77.80% / [[249, 113], [93, 473]], 
* Val   accuracy / confusion: 77.46% / [[128, 102], [31, 329]]

------------------------------ Epoch 102 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.405778
- Iter 028 / 029, Loss: 0.464042

* Train accuracy / confusion: 75.97% / [[241, 122], [101, 464]], 
* Val   accuracy / confusion: 71.86% / [[147, 83], [83, 277]]

------------------------------ Epoch 103 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.401300
- Iter 028 / 029, Loss: 0.359713

* Train accuracy / confusion: 77.37% / [[226, 138], [72, 492]], 
* Val   accuracy / confusion: 74.92% / [[114, 116], [32, 328]]

------------------------------ Epoch 104 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.433190
- Iter 028 / 029, Loss: 0.495798

* Train accuracy / confusion: 77.69% / [[246, 117], [90, 475]], 
* Val   accuracy / confusion: 74.92% / [[125, 105], [43, 317]]

------------------------------ Epoch 105 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.639521
- Iter 028 / 029, Loss: 0.359415

* Train accuracy / confusion: 76.40% / [[235, 128], [91, 474]], 
* Val   accuracy / confusion: 73.39% / [[158, 72], [85, 275]]

------------------------------ Epoch 106 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.618396
- Iter 028 / 029, Loss: 0.531591

* Train accuracy / confusion: 75.54% / [[225, 138], [89, 476]], 
* Val   accuracy / confusion: 75.59% / [[126, 104], [40, 320]]

------------------------------ Epoch 107 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.591650
- Iter 028 / 029, Loss: 0.418108

* Train accuracy / confusion: 76.72% / [[236, 128], [88, 476]], 
* Val   accuracy / confusion: 74.07% / [[174, 56], [97, 263]]

------------------------------ Epoch 108 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.451980
- Iter 028 / 029, Loss: 0.411743

* Train accuracy / confusion: 76.72% / [[237, 127], [89, 475]], 
* Val   accuracy / confusion: 75.25% / [[128, 102], [44, 316]]

------------------------------ Epoch 109 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.556077
- Iter 028 / 029, Loss: 0.632576

* Train accuracy / confusion: 76.94% / [[212, 146], [68, 502]], 
* Val   accuracy / confusion: 74.07% / [[142, 88], [65, 295]]

------------------------------ Epoch 110 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.441070
- Iter 028 / 029, Loss: 0.434506

* Train accuracy / confusion: 77.59% / [[245, 112], [96, 475]], 
* Val   accuracy / confusion: 77.29% / [[132, 98], [36, 324]]

------------------------------ Epoch 111 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.470521
- Iter 028 / 029, Loss: 0.434859

* Train accuracy / confusion: 77.91% / [[236, 126], [79, 487]], 
* Val   accuracy / confusion: 74.75% / [[112, 118], [31, 329]]

------------------------------ Epoch 112 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.526072
- Iter 028 / 029, Loss: 0.568176

* Train accuracy / confusion: 75.11% / [[223, 137], [94, 474]], 
* Val   accuracy / confusion: 66.27% / [[185, 45], [154, 206]]

------------------------------ Epoch 113 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.501058
- Iter 028 / 029, Loss: 0.329307

* Train accuracy / confusion: 76.29% / [[224, 137], [83, 484]], 
* Val   accuracy / confusion: 74.41% / [[135, 95], [56, 304]]

------------------------------ Epoch 114 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.478989
- Iter 028 / 029, Loss: 0.588478

* Train accuracy / confusion: 76.19% / [[239, 123], [98, 468]], 
* Val   accuracy / confusion: 76.61% / [[125, 105], [33, 327]]

------------------------------ Epoch 115 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.347963
- Iter 028 / 029, Loss: 0.786324

* Train accuracy / confusion: 75.97% / [[217, 145], [78, 488]], 
* Val   accuracy / confusion: 71.69% / [[134, 96], [71, 289]]

------------------------------ Epoch 116 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.396239
- Iter 028 / 029, Loss: 0.595580

* Train accuracy / confusion: 77.91% / [[244, 119], [86, 479]], 
* Val   accuracy / confusion: 75.25% / [[159, 71], [75, 285]]

------------------------------ Epoch 117 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.385247
- Iter 028 / 029, Loss: 0.414658

* Train accuracy / confusion: 77.26% / [[241, 121], [90, 476]], 
* Val   accuracy / confusion: 73.56% / [[143, 87], [69, 291]]

------------------------------ Epoch 118 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.665694
- Iter 028 / 029, Loss: 0.365169

* Train accuracy / confusion: 77.05% / [[234, 127], [86, 481]], 
* Val   accuracy / confusion: 74.41% / [[149, 81], [70, 290]]

------------------------------ Epoch 119 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.583692
- Iter 028 / 029, Loss: 0.437262

* Train accuracy / confusion: 76.51% / [[223, 134], [84, 487]], 
* Val   accuracy / confusion: 71.53% / [[133, 97], [71, 289]]

------------------------------ Epoch 120 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.392352
- Iter 028 / 029, Loss: 0.517217

* Train accuracy / confusion: 77.91% / [[247, 114], [91, 476]], 
* Val   accuracy / confusion: 71.53% / [[153, 77], [91, 269]]

------------------------------ Epoch 121 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.518908
- Iter 028 / 029, Loss: 0.491713

* Train accuracy / confusion: 77.69% / [[247, 114], [93, 474]], 
* Val   accuracy / confusion: 73.56% / [[145, 85], [71, 289]]

------------------------------ Epoch 122 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.480852
- Iter 028 / 029, Loss: 0.508742

* Train accuracy / confusion: 79.20% / [[238, 122], [71, 497]], 
* Val   accuracy / confusion: 72.88% / [[124, 106], [54, 306]]

------------------------------ Epoch 123 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.353265
- Iter 028 / 029, Loss: 0.641570

* Train accuracy / confusion: 76.94% / [[223, 136], [78, 491]], 
* Val   accuracy / confusion: 72.54% / [[157, 73], [89, 271]]

------------------------------ Epoch 124 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.412329
- Iter 028 / 029, Loss: 0.350854

* Train accuracy / confusion: 77.05% / [[239, 120], [93, 476]], 
* Val   accuracy / confusion: 73.73% / [[129, 101], [54, 306]]

------------------------------ Epoch 125 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.429985
- Iter 028 / 029, Loss: 0.467732

* Train accuracy / confusion: 76.72% / [[234, 129], [87, 478]], 
* Val   accuracy / confusion: 72.20% / [[140, 90], [74, 286]]

------------------------------ Epoch 126 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.568819
- Iter 028 / 029, Loss: 0.641667

* Train accuracy / confusion: 77.37% / [[224, 137], [73, 494]], 
* Val   accuracy / confusion: 73.73% / [[127, 103], [52, 308]]

------------------------------ Epoch 127 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.542055
- Iter 028 / 029, Loss: 0.385817

* Train accuracy / confusion: 78.77% / [[243, 118], [79, 488]], 
* Val   accuracy / confusion: 73.90% / [[149, 81], [73, 287]]

------------------------------ Epoch 128 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.393545
- Iter 028 / 029, Loss: 0.355786

* Train accuracy / confusion: 76.94% / [[224, 133], [81, 490]], 
* Val   accuracy / confusion: 72.37% / [[105, 125], [38, 322]]

------------------------------ Epoch 129 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.451413
- Iter 028 / 029, Loss: 0.500196

* Train accuracy / confusion: 77.26% / [[227, 132], [79, 490]], 
* Val   accuracy / confusion: 74.07% / [[155, 75], [78, 282]]

------------------------------ Epoch 130 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.553584
- Iter 028 / 029, Loss: 0.501815

* Train accuracy / confusion: 76.40% / [[215, 146], [73, 494]], 
* Val   accuracy / confusion: 74.24% / [[111, 119], [33, 327]]

------------------------------ Epoch 131 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.456186
- Iter 028 / 029, Loss: 0.311944

* Train accuracy / confusion: 78.99% / [[250, 109], [86, 483]], 
* Val   accuracy / confusion: 70.85% / [[142, 88], [84, 276]]

------------------------------ Epoch 132 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.426160
- Iter 028 / 029, Loss: 0.534353

* Train accuracy / confusion: 76.40% / [[232, 130], [89, 477]], 
* Val   accuracy / confusion: 74.24% / [[120, 110], [42, 318]]

------------------------------ Epoch 133 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.502366
- Iter 028 / 029, Loss: 0.471591

* Train accuracy / confusion: 77.37% / [[223, 142], [68, 495]], 
* Val   accuracy / confusion: 72.20% / [[140, 90], [74, 286]]

------------------------------ Epoch 134 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.589523
- Iter 028 / 029, Loss: 0.494793

* Train accuracy / confusion: 77.91% / [[231, 128], [77, 492]], 
* Val   accuracy / confusion: 73.90% / [[146, 84], [70, 290]]

------------------------------ Epoch 135 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.776718
- Iter 028 / 029, Loss: 0.523945

* Train accuracy / confusion: 76.19% / [[234, 131], [90, 473]], 
* Val   accuracy / confusion: 74.75% / [[144, 86], [63, 297]]

------------------------------ Epoch 136 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.353653
- Iter 028 / 029, Loss: 0.466899

* Train accuracy / confusion: 79.31% / [[242, 120], [72, 494]], 
* Val   accuracy / confusion: 75.08% / [[131, 99], [48, 312]]

------------------------------ Epoch 137 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.458354
- Iter 028 / 029, Loss: 0.456072

* Train accuracy / confusion: 77.48% / [[238, 124], [85, 481]], 
* Val   accuracy / confusion: 73.73% / [[140, 90], [65, 295]]

------------------------------ Epoch 138 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.466041
- Iter 028 / 029, Loss: 0.433754

* Train accuracy / confusion: 78.77% / [[248, 112], [85, 483]], 
* Val   accuracy / confusion: 70.34% / [[153, 77], [98, 262]]

------------------------------ Epoch 139 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.692836
- Iter 028 / 029, Loss: 0.536608

* Train accuracy / confusion: 75.97% / [[210, 149], [74, 495]], 
* Val   accuracy / confusion: 74.41% / [[130, 100], [51, 309]]

------------------------------ Epoch 140 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.547553
- Iter 028 / 029, Loss: 0.500338

* Train accuracy / confusion: 77.69% / [[247, 118], [89, 474]], 
* Val   accuracy / confusion: 72.03% / [[145, 85], [80, 280]]

------------------------------ Epoch 141 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.450882
- Iter 028 / 029, Loss: 0.731702

* Train accuracy / confusion: 77.69% / [[239, 119], [88, 482]], 
* Val   accuracy / confusion: 74.07% / [[129, 101], [52, 308]]

------------------------------ Epoch 142 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.428456
- Iter 028 / 029, Loss: 0.553867

* Train accuracy / confusion: 78.34% / [[241, 122], [79, 486]], 
* Val   accuracy / confusion: 74.75% / [[138, 92], [57, 303]]

------------------------------ Epoch 143 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.459609
- Iter 028 / 029, Loss: 0.531137

* Train accuracy / confusion: 76.83% / [[225, 132], [83, 488]], 
* Val   accuracy / confusion: 69.66% / [[96, 134], [45, 315]]

------------------------------ Epoch 144 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.393156
- Iter 028 / 029, Loss: 0.350490

* Train accuracy / confusion: 77.48% / [[230, 131], [78, 489]], 
* Val   accuracy / confusion: 73.73% / [[150, 80], [75, 285]]

------------------------------ Epoch 145 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.429979
- Iter 028 / 029, Loss: 0.471414

* Train accuracy / confusion: 77.80% / [[231, 129], [77, 491]], 
* Val   accuracy / confusion: 74.58% / [[136, 94], [56, 304]]

------------------------------ Epoch 146 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.535407
- Iter 028 / 029, Loss: 0.498909

* Train accuracy / confusion: 77.91% / [[239, 122], [83, 484]], 
* Val   accuracy / confusion: 73.73% / [[129, 101], [54, 306]]

------------------------------ Epoch 147 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.713842
- Iter 028 / 029, Loss: 0.467538

* Train accuracy / confusion: 77.26% / [[237, 123], [88, 480]], 
* Val   accuracy / confusion: 73.73% / [[163, 67], [88, 272]]

------------------------------ Epoch 148 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.459075
- Iter 028 / 029, Loss: 0.479708

* Train accuracy / confusion: 77.91% / [[237, 126], [79, 486]], 
* Val   accuracy / confusion: 75.59% / [[132, 98], [46, 314]]

------------------------------ Epoch 149 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.536430
- Iter 028 / 029, Loss: 0.418803

* Train accuracy / confusion: 77.26% / [[232, 127], [84, 485]], 
* Val   accuracy / confusion: 74.41% / [[120, 110], [41, 319]]

------------------------------ Epoch 150 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.646911
- Iter 028 / 029, Loss: 0.501914

* Train accuracy / confusion: 76.83% / [[227, 137], [78, 486]], 
* Val   accuracy / confusion: 72.88% / [[132, 98], [62, 298]]

------------------------------ Epoch 151 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.468422
- Iter 028 / 029, Loss: 0.431433

* Train accuracy / confusion: 75.97% / [[225, 137], [86, 480]], 
* Val   accuracy / confusion: 75.93% / [[149, 81], [61, 299]]

------------------------------ Epoch 152 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.343869
- Iter 028 / 029, Loss: 0.450140

* Train accuracy / confusion: 75.86% / [[224, 141], [83, 480]], 
* Val   accuracy / confusion: 74.24% / [[130, 100], [52, 308]]

------------------------------ Epoch 153 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.570454
- Iter 028 / 029, Loss: 0.475184

* Train accuracy / confusion: 77.59% / [[237, 126], [82, 483]], 
* Val   accuracy / confusion: 74.07% / [[151, 79], [74, 286]]

------------------------------ Epoch 154 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.436480
- Iter 028 / 029, Loss: 0.387715

* Train accuracy / confusion: 76.94% / [[232, 132], [82, 482]], 
* Val   accuracy / confusion: 73.22% / [[93, 137], [21, 339]]

------------------------------ Epoch 155 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.495438
- Iter 028 / 029, Loss: 0.400099

* Train accuracy / confusion: 78.23% / [[244, 119], [83, 482]], 
* Val   accuracy / confusion: 73.05% / [[148, 82], [77, 283]]

------------------------------ Epoch 156 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.453451
- Iter 028 / 029, Loss: 0.320825

* Train accuracy / confusion: 77.91% / [[232, 129], [76, 491]], 
* Val   accuracy / confusion: 72.20% / [[130, 100], [64, 296]]

------------------------------ Epoch 157 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.331059
- Iter 028 / 029, Loss: 0.404265

* Train accuracy / confusion: 78.45% / [[250, 109], [91, 478]], 
* Val   accuracy / confusion: 72.37% / [[142, 88], [75, 285]]

------------------------------ Epoch 158 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.529685
- Iter 028 / 029, Loss: 0.431136

* Train accuracy / confusion: 77.80% / [[229, 133], [73, 493]], 
* Val   accuracy / confusion: 74.92% / [[139, 91], [57, 303]]

------------------------------ Epoch 159 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.451557
- Iter 028 / 029, Loss: 0.453181

* Train accuracy / confusion: 77.05% / [[236, 125], [88, 479]], 
* Val   accuracy / confusion: 68.98% / [[154, 76], [107, 253]]

------------------------------ Epoch 160 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.469417
- Iter 028 / 029, Loss: 0.524808

* Train accuracy / confusion: 77.05% / [[229, 132], [81, 486]], 
* Val   accuracy / confusion: 72.37% / [[142, 88], [75, 285]]

------------------------------ Epoch 161 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.585358
- Iter 028 / 029, Loss: 0.363034

* Train accuracy / confusion: 78.12% / [[235, 127], [76, 490]], 
* Val   accuracy / confusion: 74.41% / [[131, 99], [52, 308]]

------------------------------ Epoch 162 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.617065
- Iter 028 / 029, Loss: 0.520208

* Train accuracy / confusion: 75.43% / [[234, 130], [98, 466]], 
* Val   accuracy / confusion: 74.58% / [[141, 89], [61, 299]]

------------------------------ Epoch 163 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.585363
- Iter 028 / 029, Loss: 0.682366

* Train accuracy / confusion: 77.05% / [[232, 123], [90, 483]], 
* Val   accuracy / confusion: 72.03% / [[141, 89], [76, 284]]

------------------------------ Epoch 164 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.572904
- Iter 028 / 029, Loss: 0.337293

* Train accuracy / confusion: 78.99% / [[238, 123], [72, 495]], 
* Val   accuracy / confusion: 74.75% / [[152, 78], [71, 289]]

------------------------------ Epoch 165 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.388123
- Iter 028 / 029, Loss: 0.484769

* Train accuracy / confusion: 77.91% / [[244, 120], [85, 479]], 
* Val   accuracy / confusion: 72.20% / [[162, 68], [96, 264]]

------------------------------ Epoch 166 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.508077
- Iter 028 / 029, Loss: 0.836212

* Train accuracy / confusion: 77.80% / [[232, 131], [75, 490]], 
* Val   accuracy / confusion: 73.90% / [[109, 121], [33, 327]]

------------------------------ Epoch 167 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.374466
- Iter 028 / 029, Loss: 0.467359

* Train accuracy / confusion: 76.51% / [[223, 143], [75, 487]], 
* Val   accuracy / confusion: 76.61% / [[133, 97], [41, 319]]

------------------------------ Epoch 168 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.537741
- Iter 028 / 029, Loss: 0.677388

* Train accuracy / confusion: 77.37% / [[242, 123], [87, 476]], 
* Val   accuracy / confusion: 75.93% / [[150, 80], [62, 298]]

------------------------------ Epoch 169 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.487610
- Iter 028 / 029, Loss: 0.522652

* Train accuracy / confusion: 77.37% / [[240, 124], [86, 478]], 
* Val   accuracy / confusion: 74.24% / [[169, 61], [91, 269]]

------------------------------ Epoch 170 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.709485
- Iter 028 / 029, Loss: 0.560517

* Train accuracy / confusion: 76.94% / [[228, 134], [80, 486]], 
* Val   accuracy / confusion: 73.22% / [[132, 98], [60, 300]]

------------------------------ Epoch 171 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.489354
- Iter 028 / 029, Loss: 0.395028

* Train accuracy / confusion: 78.02% / [[233, 127], [77, 491]], 
* Val   accuracy / confusion: 71.86% / [[159, 71], [95, 265]]

------------------------------ Epoch 172 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.372398
- Iter 028 / 029, Loss: 0.685245

* Train accuracy / confusion: 77.91% / [[245, 119], [86, 478]], 
* Val   accuracy / confusion: 74.75% / [[141, 89], [60, 300]]

------------------------------ Epoch 173 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.402504
- Iter 028 / 029, Loss: 0.678126

* Train accuracy / confusion: 77.37% / [[238, 125], [85, 480]], 
* Val   accuracy / confusion: 73.90% / [[138, 92], [62, 298]]

------------------------------ Epoch 174 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.602438
- Iter 028 / 029, Loss: 0.372157

* Train accuracy / confusion: 78.88% / [[241, 119], [77, 491]], 
* Val   accuracy / confusion: 71.86% / [[166, 64], [102, 258]]

------------------------------ Epoch 175 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.369122
- Iter 028 / 029, Loss: 0.430445

* Train accuracy / confusion: 77.69% / [[240, 124], [83, 481]], 
* Val   accuracy / confusion: 74.07% / [[115, 115], [38, 322]]

------------------------------ Epoch 176 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.335590
- Iter 028 / 029, Loss: 0.455288

* Train accuracy / confusion: 76.94% / [[241, 120], [94, 473]], 
* Val   accuracy / confusion: 74.92% / [[147, 83], [65, 295]]

------------------------------ Epoch 177 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.545812
- Iter 028 / 029, Loss: 0.377319

* Train accuracy / confusion: 77.80% / [[231, 127], [79, 491]], 
* Val   accuracy / confusion: 75.76% / [[126, 104], [39, 321]]

------------------------------ Epoch 178 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.297183
- Iter 028 / 029, Loss: 0.465672

* Train accuracy / confusion: 78.56% / [[243, 119], [80, 486]], 
* Val   accuracy / confusion: 75.08% / [[139, 91], [56, 304]]

------------------------------ Epoch 179 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.331991
- Iter 028 / 029, Loss: 0.491276

* Train accuracy / confusion: 78.12% / [[243, 120], [83, 482]], 
* Val   accuracy / confusion: 74.07% / [[155, 75], [78, 282]]

------------------------------ Epoch 180 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.266149
- Iter 028 / 029, Loss: 0.452006

* Train accuracy / confusion: 78.66% / [[240, 122], [76, 490]], 
* Val   accuracy / confusion: 73.90% / [[162, 68], [86, 274]]

------------------------------ Epoch 181 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.597618
- Iter 028 / 029, Loss: 0.361078

* Train accuracy / confusion: 79.63% / [[253, 107], [82, 486]], 
* Val   accuracy / confusion: 72.54% / [[144, 86], [76, 284]]

------------------------------ Epoch 182 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.369757
- Iter 028 / 029, Loss: 0.292805

* Train accuracy / confusion: 78.45% / [[256, 108], [92, 472]], 
* Val   accuracy / confusion: 72.71% / [[150, 80], [81, 279]]

------------------------------ Epoch 183 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.414444
- Iter 028 / 029, Loss: 0.348370

* Train accuracy / confusion: 79.31% / [[244, 117], [75, 492]], 
* Val   accuracy / confusion: 72.54% / [[141, 89], [73, 287]]

------------------------------ Epoch 184 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.448002
- Iter 028 / 029, Loss: 0.482946

* Train accuracy / confusion: 78.88% / [[263, 102], [94, 469]], 
* Val   accuracy / confusion: 71.86% / [[132, 98], [68, 292]]

------------------------------ Epoch 185 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.572643
- Iter 028 / 029, Loss: 0.679665

* Train accuracy / confusion: 77.48% / [[221, 139], [70, 498]], 
* Val   accuracy / confusion: 72.03% / [[133, 97], [68, 292]]

------------------------------ Epoch 186 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.577922
- Iter 028 / 029, Loss: 0.565541

* Train accuracy / confusion: 78.02% / [[240, 120], [84, 484]], 
* Val   accuracy / confusion: 74.24% / [[141, 89], [63, 297]]

------------------------------ Epoch 187 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.452846
- Iter 028 / 029, Loss: 0.421333

* Train accuracy / confusion: 77.91% / [[241, 124], [81, 482]], 
* Val   accuracy / confusion: 71.36% / [[130, 100], [69, 291]]

------------------------------ Epoch 188 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.448886
- Iter 028 / 029, Loss: 0.352031

* Train accuracy / confusion: 77.48% / [[229, 131], [78, 490]], 
* Val   accuracy / confusion: 71.53% / [[123, 107], [61, 299]]

------------------------------ Epoch 189 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.409348
- Iter 028 / 029, Loss: 0.543845

* Train accuracy / confusion: 76.51% / [[229, 133], [85, 481]], 
* Val   accuracy / confusion: 73.56% / [[129, 101], [55, 305]]

------------------------------ Epoch 190 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.435826
- Iter 028 / 029, Loss: 0.494455

* Train accuracy / confusion: 78.02% / [[238, 125], [79, 486]], 
* Val   accuracy / confusion: 71.53% / [[170, 60], [108, 252]]

------------------------------ Epoch 191 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.442677
- Iter 028 / 029, Loss: 0.375017

* Train accuracy / confusion: 78.77% / [[258, 107], [90, 473]], 
* Val   accuracy / confusion: 74.07% / [[131, 99], [54, 306]]

------------------------------ Epoch 192 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.595005
- Iter 028 / 029, Loss: 0.616578

* Train accuracy / confusion: 77.91% / [[237, 126], [79, 486]], 
* Val   accuracy / confusion: 74.07% / [[134, 96], [57, 303]]

------------------------------ Epoch 193 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.525545
- Iter 028 / 029, Loss: 0.417832

* Train accuracy / confusion: 77.59% / [[240, 121], [87, 480]], 
* Val   accuracy / confusion: 74.75% / [[133, 97], [52, 308]]

------------------------------ Epoch 194 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.377137
- Iter 028 / 029, Loss: 0.405476

* Train accuracy / confusion: 78.45% / [[239, 123], [77, 489]], 
* Val   accuracy / confusion: 72.54% / [[135, 95], [67, 293]]

------------------------------ Epoch 195 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.342741
- Iter 028 / 029, Loss: 0.685691

* Train accuracy / confusion: 78.88% / [[247, 115], [81, 485]], 
* Val   accuracy / confusion: 73.90% / [[124, 106], [48, 312]]

------------------------------ Epoch 196 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.598929
- Iter 028 / 029, Loss: 0.423541

* Train accuracy / confusion: 79.31% / [[254, 110], [82, 482]], 
* Val   accuracy / confusion: 71.69% / [[131, 99], [68, 292]]

------------------------------ Epoch 197 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.564700
- Iter 028 / 029, Loss: 0.540049

* Train accuracy / confusion: 78.12% / [[240, 119], [84, 485]], 
* Val   accuracy / confusion: 72.54% / [[133, 97], [65, 295]]

------------------------------ Epoch 198 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.435314
- Iter 028 / 029, Loss: 0.466770

* Train accuracy / confusion: 80.71% / [[247, 115], [64, 502]], 
* Val   accuracy / confusion: 73.90% / [[155, 75], [79, 281]]

------------------------------ Epoch 199 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.638351
- Iter 028 / 029, Loss: 0.365382

* Train accuracy / confusion: 77.16% / [[233, 129], [83, 483]], 
* Val   accuracy / confusion: 74.24% / [[133, 97], [55, 305]]

------------------------------ Epoch 200 / 500, Learning rate: 1.92e-03 ------------------------------
- Iter 014 / 029, Loss: 0.567748
- Iter 028 / 029, Loss: 0.703160

* Train accuracy / confusion: 78.34% / [[239, 124], [77, 488]], 
* Val   accuracy / confusion: 72.20% / [[129, 101], [63, 297]]

------------------------------ Epoch 201 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.481995
- Iter 028 / 029, Loss: 0.407458

* Train accuracy / confusion: 79.09% / [[248, 113], [81, 486]], 
* Val   accuracy / confusion: 75.25% / [[155, 75], [71, 289]]

------------------------------ Epoch 202 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.558477
- Iter 028 / 029, Loss: 0.357850

* Train accuracy / confusion: 79.31% / [[253, 110], [82, 483]], 
* Val   accuracy / confusion: 70.00% / [[135, 95], [82, 278]]

------------------------------ Epoch 203 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.446405
- Iter 028 / 029, Loss: 0.439719

* Train accuracy / confusion: 79.42% / [[251, 114], [77, 486]], 
* Val   accuracy / confusion: 71.53% / [[133, 97], [71, 289]]

------------------------------ Epoch 204 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.547564
- Iter 028 / 029, Loss: 0.456539

* Train accuracy / confusion: 80.06% / [[251, 116], [69, 492]], 
* Val   accuracy / confusion: 72.03% / [[129, 101], [64, 296]]

------------------------------ Epoch 205 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.536004
- Iter 028 / 029, Loss: 0.444154

* Train accuracy / confusion: 80.06% / [[258, 104], [81, 485]], 
* Val   accuracy / confusion: 74.07% / [[144, 86], [67, 293]]

------------------------------ Epoch 206 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.386795
- Iter 028 / 029, Loss: 0.553015

* Train accuracy / confusion: 78.66% / [[245, 115], [83, 485]], 
* Val   accuracy / confusion: 75.25% / [[151, 79], [67, 293]]

------------------------------ Epoch 207 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.470391
- Iter 028 / 029, Loss: 0.489517

* Train accuracy / confusion: 77.59% / [[240, 122], [86, 480]], 
* Val   accuracy / confusion: 73.05% / [[148, 82], [77, 283]]

------------------------------ Epoch 208 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.394934
- Iter 028 / 029, Loss: 0.706627

* Train accuracy / confusion: 78.88% / [[244, 120], [76, 488]], 
* Val   accuracy / confusion: 73.05% / [[142, 88], [71, 289]]

------------------------------ Epoch 209 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.578795
- Iter 028 / 029, Loss: 0.629795

* Train accuracy / confusion: 78.99% / [[246, 115], [80, 487]], 
* Val   accuracy / confusion: 73.56% / [[143, 87], [69, 291]]

------------------------------ Epoch 210 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.370295
- Iter 028 / 029, Loss: 0.435172

* Train accuracy / confusion: 78.23% / [[241, 120], [82, 485]], 
* Val   accuracy / confusion: 74.07% / [[138, 92], [61, 299]]

------------------------------ Epoch 211 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.513562
- Iter 028 / 029, Loss: 0.582146

* Train accuracy / confusion: 78.77% / [[247, 116], [81, 484]], 
* Val   accuracy / confusion: 74.75% / [[138, 92], [57, 303]]

------------------------------ Epoch 212 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.447022
- Iter 028 / 029, Loss: 0.459862

* Train accuracy / confusion: 79.31% / [[250, 112], [80, 486]], 
* Val   accuracy / confusion: 74.75% / [[144, 86], [63, 297]]

------------------------------ Epoch 213 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.444173
- Iter 028 / 029, Loss: 0.361794

* Train accuracy / confusion: 79.42% / [[249, 109], [82, 488]], 
* Val   accuracy / confusion: 73.73% / [[143, 87], [68, 292]]

------------------------------ Epoch 214 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.521739
- Iter 028 / 029, Loss: 0.416395

* Train accuracy / confusion: 80.60% / [[253, 111], [69, 495]], 
* Val   accuracy / confusion: 71.69% / [[140, 90], [77, 283]]

------------------------------ Epoch 215 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.448439
- Iter 028 / 029, Loss: 0.546322

* Train accuracy / confusion: 79.09% / [[248, 114], [80, 486]], 
* Val   accuracy / confusion: 73.73% / [[137, 93], [62, 298]]

------------------------------ Epoch 216 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.403061
- Iter 028 / 029, Loss: 0.439311

* Train accuracy / confusion: 80.17% / [[260, 105], [79, 484]], 
* Val   accuracy / confusion: 73.05% / [[138, 92], [67, 293]]

------------------------------ Epoch 217 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.377643
- Iter 028 / 029, Loss: 0.618030

* Train accuracy / confusion: 78.34% / [[253, 113], [88, 474]], 
* Val   accuracy / confusion: 73.73% / [[141, 89], [66, 294]]

------------------------------ Epoch 218 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.480961
- Iter 028 / 029, Loss: 0.376299

* Train accuracy / confusion: 79.85% / [[256, 108], [79, 485]], 
* Val   accuracy / confusion: 71.69% / [[138, 92], [75, 285]]

------------------------------ Epoch 219 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.384315
- Iter 028 / 029, Loss: 0.277055

* Train accuracy / confusion: 79.53% / [[256, 108], [82, 482]], 
* Val   accuracy / confusion: 72.37% / [[152, 78], [85, 275]]

------------------------------ Epoch 220 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.360168
- Iter 028 / 029, Loss: 0.496145

* Train accuracy / confusion: 78.99% / [[252, 112], [83, 481]], 
* Val   accuracy / confusion: 72.88% / [[143, 87], [73, 287]]

------------------------------ Epoch 221 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.539879
- Iter 028 / 029, Loss: 0.503718

* Train accuracy / confusion: 78.99% / [[247, 114], [81, 486]], 
* Val   accuracy / confusion: 73.73% / [[148, 82], [73, 287]]

------------------------------ Epoch 222 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.410571
- Iter 028 / 029, Loss: 0.486147

* Train accuracy / confusion: 78.66% / [[249, 112], [86, 481]], 
* Val   accuracy / confusion: 72.54% / [[149, 81], [81, 279]]

------------------------------ Epoch 223 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.347635
- Iter 028 / 029, Loss: 0.520536

* Train accuracy / confusion: 79.85% / [[254, 108], [79, 487]], 
* Val   accuracy / confusion: 72.03% / [[135, 95], [70, 290]]

------------------------------ Epoch 224 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.543851
- Iter 028 / 029, Loss: 0.420293

* Train accuracy / confusion: 79.42% / [[251, 111], [80, 486]], 
* Val   accuracy / confusion: 73.56% / [[144, 86], [70, 290]]

------------------------------ Epoch 225 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.448507
- Iter 028 / 029, Loss: 0.346060

* Train accuracy / confusion: 80.93% / [[252, 111], [66, 499]], 
* Val   accuracy / confusion: 74.24% / [[136, 94], [58, 302]]

------------------------------ Epoch 226 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.332011
- Iter 028 / 029, Loss: 0.353624

* Train accuracy / confusion: 79.96% / [[260, 100], [86, 482]], 
* Val   accuracy / confusion: 72.54% / [[144, 86], [76, 284]]

------------------------------ Epoch 227 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.742108
- Iter 028 / 029, Loss: 0.359894

* Train accuracy / confusion: 78.77% / [[242, 117], [80, 489]], 
* Val   accuracy / confusion: 74.41% / [[146, 84], [67, 293]]

------------------------------ Epoch 228 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.525990
- Iter 028 / 029, Loss: 0.532835

* Train accuracy / confusion: 78.12% / [[247, 113], [90, 478]], 
* Val   accuracy / confusion: 76.27% / [[149, 81], [59, 301]]

------------------------------ Epoch 229 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.360543
- Iter 028 / 029, Loss: 0.395978

* Train accuracy / confusion: 80.39% / [[249, 115], [67, 497]], 
* Val   accuracy / confusion: 73.05% / [[145, 85], [74, 286]]

------------------------------ Epoch 230 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.514258
- Iter 028 / 029, Loss: 0.395047

* Train accuracy / confusion: 79.85% / [[245, 115], [72, 496]], 
* Val   accuracy / confusion: 72.20% / [[137, 93], [71, 289]]

------------------------------ Epoch 231 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.512472
- Iter 028 / 029, Loss: 0.368686

* Train accuracy / confusion: 78.34% / [[244, 118], [83, 483]], 
* Val   accuracy / confusion: 73.05% / [[141, 89], [70, 290]]

------------------------------ Epoch 232 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.539943
- Iter 028 / 029, Loss: 0.280065

* Train accuracy / confusion: 81.57% / [[257, 99], [72, 500]], 
* Val   accuracy / confusion: 71.36% / [[143, 87], [82, 278]]

------------------------------ Epoch 233 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.340337
- Iter 028 / 029, Loss: 0.394597

* Train accuracy / confusion: 78.56% / [[242, 117], [82, 487]], 
* Val   accuracy / confusion: 74.07% / [[148, 82], [71, 289]]

------------------------------ Epoch 234 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.319521
- Iter 028 / 029, Loss: 0.438940

* Train accuracy / confusion: 80.60% / [[256, 106], [74, 492]], 
* Val   accuracy / confusion: 73.56% / [[145, 85], [71, 289]]

------------------------------ Epoch 235 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.322948
- Iter 028 / 029, Loss: 0.475488

* Train accuracy / confusion: 78.88% / [[248, 113], [83, 484]], 
* Val   accuracy / confusion: 73.22% / [[139, 91], [67, 293]]

------------------------------ Epoch 236 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.376511
- Iter 028 / 029, Loss: 0.444967

* Train accuracy / confusion: 81.03% / [[262, 101], [75, 490]], 
* Val   accuracy / confusion: 73.56% / [[142, 88], [68, 292]]

------------------------------ Epoch 237 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.404006
- Iter 028 / 029, Loss: 0.418996

* Train accuracy / confusion: 79.63% / [[251, 112], [77, 488]], 
* Val   accuracy / confusion: 73.22% / [[142, 88], [70, 290]]

------------------------------ Epoch 238 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.431799
- Iter 028 / 029, Loss: 0.469531

* Train accuracy / confusion: 79.96% / [[254, 110], [76, 488]], 
* Val   accuracy / confusion: 72.03% / [[145, 85], [80, 280]]

------------------------------ Epoch 239 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.503850
- Iter 028 / 029, Loss: 0.476457

* Train accuracy / confusion: 82.22% / [[262, 99], [66, 501]], 
* Val   accuracy / confusion: 72.03% / [[145, 85], [80, 280]]

------------------------------ Epoch 240 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.425273
- Iter 028 / 029, Loss: 0.443642

* Train accuracy / confusion: 81.47% / [[258, 102], [70, 498]], 
* Val   accuracy / confusion: 72.20% / [[139, 91], [73, 287]]

------------------------------ Epoch 241 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.762679
- Iter 028 / 029, Loss: 0.291245

* Train accuracy / confusion: 79.53% / [[256, 106], [84, 482]], 
* Val   accuracy / confusion: 72.20% / [[146, 84], [80, 280]]

------------------------------ Epoch 242 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.627124
- Iter 028 / 029, Loss: 0.400233

* Train accuracy / confusion: 79.96% / [[252, 109], [77, 490]], 
* Val   accuracy / confusion: 72.88% / [[144, 86], [74, 286]]

------------------------------ Epoch 243 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.433089
- Iter 028 / 029, Loss: 0.448737

* Train accuracy / confusion: 80.50% / [[254, 111], [70, 493]], 
* Val   accuracy / confusion: 76.44% / [[155, 75], [64, 296]]

------------------------------ Epoch 244 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.385664
- Iter 028 / 029, Loss: 0.317505

* Train accuracy / confusion: 80.39% / [[259, 101], [81, 487]], 
* Val   accuracy / confusion: 71.86% / [[142, 88], [78, 282]]

------------------------------ Epoch 245 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.323833
- Iter 028 / 029, Loss: 0.390861

* Train accuracy / confusion: 79.96% / [[258, 106], [80, 484]], 
* Val   accuracy / confusion: 74.24% / [[139, 91], [61, 299]]

------------------------------ Epoch 246 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.481756
- Iter 028 / 029, Loss: 0.437596

* Train accuracy / confusion: 79.63% / [[247, 112], [77, 492]], 
* Val   accuracy / confusion: 73.39% / [[153, 77], [80, 280]]

------------------------------ Epoch 247 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.463495
- Iter 028 / 029, Loss: 0.356704

* Train accuracy / confusion: 80.50% / [[257, 107], [74, 490]], 
* Val   accuracy / confusion: 73.39% / [[152, 78], [79, 281]]

------------------------------ Epoch 248 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.383554
- Iter 028 / 029, Loss: 0.570787

* Train accuracy / confusion: 79.53% / [[245, 114], [76, 493]], 
* Val   accuracy / confusion: 74.75% / [[147, 83], [66, 294]]

------------------------------ Epoch 249 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.334536
- Iter 028 / 029, Loss: 0.401560

* Train accuracy / confusion: 81.25% / [[256, 106], [68, 498]], 
* Val   accuracy / confusion: 73.05% / [[145, 85], [74, 286]]

------------------------------ Epoch 250 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.340309
- Iter 028 / 029, Loss: 0.279269

* Train accuracy / confusion: 79.42% / [[247, 111], [80, 490]], 
* Val   accuracy / confusion: 71.69% / [[122, 108], [59, 301]]

------------------------------ Epoch 251 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.487567
- Iter 028 / 029, Loss: 0.482627

* Train accuracy / confusion: 78.34% / [[243, 118], [83, 484]], 
* Val   accuracy / confusion: 74.24% / [[143, 87], [65, 295]]

------------------------------ Epoch 252 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.297203
- Iter 028 / 029, Loss: 0.620756

* Train accuracy / confusion: 78.77% / [[245, 118], [79, 486]], 
* Val   accuracy / confusion: 71.86% / [[133, 97], [69, 291]]

------------------------------ Epoch 253 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.543327
- Iter 028 / 029, Loss: 0.444487

* Train accuracy / confusion: 78.88% / [[236, 125], [71, 496]], 
* Val   accuracy / confusion: 71.86% / [[139, 91], [75, 285]]

------------------------------ Epoch 254 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.382633
- Iter 028 / 029, Loss: 0.553742

* Train accuracy / confusion: 80.82% / [[262, 99], [79, 488]], 
* Val   accuracy / confusion: 73.56% / [[142, 88], [68, 292]]

------------------------------ Epoch 255 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.366754
- Iter 028 / 029, Loss: 0.395720

* Train accuracy / confusion: 81.36% / [[258, 102], [71, 497]], 
* Val   accuracy / confusion: 72.03% / [[135, 95], [70, 290]]

------------------------------ Epoch 256 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.386414
- Iter 028 / 029, Loss: 0.476649

* Train accuracy / confusion: 78.45% / [[241, 120], [80, 487]], 
* Val   accuracy / confusion: 74.92% / [[144, 86], [62, 298]]

------------------------------ Epoch 257 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.475235
- Iter 028 / 029, Loss: 0.490900

* Train accuracy / confusion: 80.17% / [[254, 108], [76, 490]], 
* Val   accuracy / confusion: 73.90% / [[143, 87], [67, 293]]

------------------------------ Epoch 258 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.247871
- Iter 028 / 029, Loss: 0.428706

* Train accuracy / confusion: 79.85% / [[257, 105], [82, 484]], 
* Val   accuracy / confusion: 73.90% / [[150, 80], [74, 286]]

------------------------------ Epoch 259 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.621706
- Iter 028 / 029, Loss: 0.530066

* Train accuracy / confusion: 81.36% / [[261, 100], [73, 494]], 
* Val   accuracy / confusion: 72.20% / [[136, 94], [70, 290]]

------------------------------ Epoch 260 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.378972
- Iter 028 / 029, Loss: 0.524603

* Train accuracy / confusion: 80.50% / [[255, 107], [74, 492]], 
* Val   accuracy / confusion: 72.37% / [[139, 91], [72, 288]]

------------------------------ Epoch 261 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.510336
- Iter 028 / 029, Loss: 0.600333

* Train accuracy / confusion: 80.71% / [[261, 100], [79, 488]], 
* Val   accuracy / confusion: 72.71% / [[135, 95], [66, 294]]

------------------------------ Epoch 262 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.299710
- Iter 028 / 029, Loss: 0.309151

* Train accuracy / confusion: 80.50% / [[260, 99], [82, 487]], 
* Val   accuracy / confusion: 72.88% / [[142, 88], [72, 288]]

------------------------------ Epoch 263 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.467291
- Iter 028 / 029, Loss: 0.445761

* Train accuracy / confusion: 80.93% / [[257, 102], [75, 494]], 
* Val   accuracy / confusion: 73.05% / [[147, 83], [76, 284]]

------------------------------ Epoch 264 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.350944
- Iter 028 / 029, Loss: 0.520914

* Train accuracy / confusion: 80.93% / [[253, 105], [72, 498]], 
* Val   accuracy / confusion: 71.19% / [[147, 83], [87, 273]]

------------------------------ Epoch 265 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.332456
- Iter 028 / 029, Loss: 0.398186

* Train accuracy / confusion: 78.99% / [[252, 110], [85, 481]], 
* Val   accuracy / confusion: 73.56% / [[143, 87], [69, 291]]

------------------------------ Epoch 266 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.370604
- Iter 028 / 029, Loss: 0.645180

* Train accuracy / confusion: 79.63% / [[245, 118], [71, 494]], 
* Val   accuracy / confusion: 73.05% / [[141, 89], [70, 290]]

------------------------------ Epoch 267 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.386330
- Iter 028 / 029, Loss: 0.442329

* Train accuracy / confusion: 78.66% / [[243, 121], [77, 487]], 
* Val   accuracy / confusion: 72.03% / [[138, 92], [73, 287]]

------------------------------ Epoch 268 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.341554
- Iter 028 / 029, Loss: 0.330356

* Train accuracy / confusion: 81.36% / [[261, 103], [70, 494]], 
* Val   accuracy / confusion: 74.41% / [[149, 81], [70, 290]]

------------------------------ Epoch 269 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.280589
- Iter 028 / 029, Loss: 0.532447

* Train accuracy / confusion: 80.06% / [[252, 111], [74, 491]], 
* Val   accuracy / confusion: 73.39% / [[140, 90], [67, 293]]

------------------------------ Epoch 270 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.267592
- Iter 028 / 029, Loss: 0.580947

* Train accuracy / confusion: 80.82% / [[253, 107], [71, 497]], 
* Val   accuracy / confusion: 75.42% / [[139, 91], [54, 306]]

------------------------------ Epoch 271 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.506930
- Iter 028 / 029, Loss: 0.704401

* Train accuracy / confusion: 79.42% / [[245, 115], [76, 492]], 
* Val   accuracy / confusion: 72.71% / [[141, 89], [72, 288]]

------------------------------ Epoch 272 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.488725
- Iter 028 / 029, Loss: 0.397067

* Train accuracy / confusion: 79.53% / [[249, 115], [75, 489]], 
* Val   accuracy / confusion: 74.92% / [[145, 85], [63, 297]]

------------------------------ Epoch 273 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.368496
- Iter 028 / 029, Loss: 0.367486

* Train accuracy / confusion: 79.31% / [[244, 118], [74, 492]], 
* Val   accuracy / confusion: 74.41% / [[144, 86], [65, 295]]

------------------------------ Epoch 274 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.322247
- Iter 028 / 029, Loss: 0.622103

* Train accuracy / confusion: 79.53% / [[248, 112], [78, 490]], 
* Val   accuracy / confusion: 71.02% / [[133, 97], [74, 286]]

------------------------------ Epoch 275 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.491364
- Iter 028 / 029, Loss: 0.356856

* Train accuracy / confusion: 78.56% / [[247, 114], [85, 482]], 
* Val   accuracy / confusion: 74.58% / [[140, 90], [60, 300]]

------------------------------ Epoch 276 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.470173
- Iter 028 / 029, Loss: 0.367843

* Train accuracy / confusion: 78.99% / [[246, 115], [80, 487]], 
* Val   accuracy / confusion: 74.07% / [[147, 83], [70, 290]]

------------------------------ Epoch 277 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.531834
- Iter 028 / 029, Loss: 0.437305

* Train accuracy / confusion: 80.06% / [[253, 112], [73, 490]], 
* Val   accuracy / confusion: 73.22% / [[137, 93], [65, 295]]

------------------------------ Epoch 278 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.538604
- Iter 028 / 029, Loss: 0.502142

* Train accuracy / confusion: 80.06% / [[248, 113], [72, 495]], 
* Val   accuracy / confusion: 73.90% / [[137, 93], [61, 299]]

------------------------------ Epoch 279 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.524242
- Iter 028 / 029, Loss: 0.409428

* Train accuracy / confusion: 80.28% / [[249, 113], [70, 496]], 
* Val   accuracy / confusion: 73.39% / [[142, 88], [69, 291]]

------------------------------ Epoch 280 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.351514
- Iter 028 / 029, Loss: 0.313851

* Train accuracy / confusion: 80.71% / [[260, 105], [74, 489]], 
* Val   accuracy / confusion: 73.56% / [[138, 92], [64, 296]]

------------------------------ Epoch 281 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.484459
- Iter 028 / 029, Loss: 0.336636

* Train accuracy / confusion: 79.53% / [[246, 117], [73, 492]], 
* Val   accuracy / confusion: 74.92% / [[142, 88], [60, 300]]

------------------------------ Epoch 282 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.486621
- Iter 028 / 029, Loss: 0.469890

* Train accuracy / confusion: 78.56% / [[243, 116], [83, 486]], 
* Val   accuracy / confusion: 74.24% / [[140, 90], [62, 298]]

------------------------------ Epoch 283 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.411789
- Iter 028 / 029, Loss: 0.344052

* Train accuracy / confusion: 78.66% / [[250, 115], [83, 480]], 
* Val   accuracy / confusion: 72.37% / [[138, 92], [71, 289]]

------------------------------ Epoch 284 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.351503
- Iter 028 / 029, Loss: 0.472522

* Train accuracy / confusion: 80.71% / [[252, 106], [73, 497]], 
* Val   accuracy / confusion: 74.24% / [[139, 91], [61, 299]]

------------------------------ Epoch 285 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.512797
- Iter 028 / 029, Loss: 0.341188

* Train accuracy / confusion: 81.25% / [[252, 108], [66, 502]], 
* Val   accuracy / confusion: 73.73% / [[150, 80], [75, 285]]

------------------------------ Epoch 286 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.426661
- Iter 028 / 029, Loss: 0.393467

* Train accuracy / confusion: 81.03% / [[259, 102], [74, 493]], 
* Val   accuracy / confusion: 73.90% / [[141, 89], [65, 295]]

------------------------------ Epoch 287 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.445883
- Iter 028 / 029, Loss: 0.407486

* Train accuracy / confusion: 79.96% / [[250, 112], [74, 492]], 
* Val   accuracy / confusion: 74.75% / [[139, 91], [58, 302]]

------------------------------ Epoch 288 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.392769
- Iter 028 / 029, Loss: 0.321230

* Train accuracy / confusion: 81.03% / [[256, 106], [70, 496]], 
* Val   accuracy / confusion: 75.08% / [[144, 86], [61, 299]]

------------------------------ Epoch 289 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.423570
- Iter 028 / 029, Loss: 0.362301

* Train accuracy / confusion: 80.39% / [[254, 106], [76, 492]], 
* Val   accuracy / confusion: 72.54% / [[145, 85], [77, 283]]

------------------------------ Epoch 290 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.513767
- Iter 028 / 029, Loss: 0.464204

* Train accuracy / confusion: 79.96% / [[254, 108], [78, 488]], 
* Val   accuracy / confusion: 73.90% / [[139, 91], [63, 297]]

------------------------------ Epoch 291 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.431384
- Iter 028 / 029, Loss: 0.681143

* Train accuracy / confusion: 80.06% / [[248, 113], [72, 495]], 
* Val   accuracy / confusion: 72.37% / [[127, 103], [60, 300]]

------------------------------ Epoch 292 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.505968
- Iter 028 / 029, Loss: 0.408369

* Train accuracy / confusion: 81.36% / [[254, 107], [66, 501]], 
* Val   accuracy / confusion: 73.73% / [[138, 92], [63, 297]]

------------------------------ Epoch 293 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.364634
- Iter 028 / 029, Loss: 0.473638

* Train accuracy / confusion: 80.93% / [[253, 109], [68, 498]], 
* Val   accuracy / confusion: 74.92% / [[140, 90], [58, 302]]

------------------------------ Epoch 294 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.460724
- Iter 028 / 029, Loss: 0.565774

* Train accuracy / confusion: 80.50% / [[254, 109], [72, 493]], 
* Val   accuracy / confusion: 71.53% / [[139, 91], [77, 283]]

------------------------------ Epoch 295 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.512318
- Iter 028 / 029, Loss: 0.666361

* Train accuracy / confusion: 80.82% / [[258, 103], [75, 492]], 
* Val   accuracy / confusion: 73.56% / [[147, 83], [73, 287]]

------------------------------ Epoch 296 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.458033
- Iter 028 / 029, Loss: 0.387485

* Train accuracy / confusion: 80.71% / [[257, 103], [76, 492]], 
* Val   accuracy / confusion: 72.37% / [[137, 93], [70, 290]]

------------------------------ Epoch 297 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.429127
- Iter 028 / 029, Loss: 0.450515

* Train accuracy / confusion: 80.17% / [[246, 114], [70, 498]], 
* Val   accuracy / confusion: 71.53% / [[148, 82], [86, 274]]

------------------------------ Epoch 298 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.474242
- Iter 028 / 029, Loss: 0.493947

* Train accuracy / confusion: 79.85% / [[248, 114], [73, 493]], 
* Val   accuracy / confusion: 73.22% / [[133, 97], [61, 299]]

------------------------------ Epoch 299 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.586320
- Iter 028 / 029, Loss: 0.322967

* Train accuracy / confusion: 80.17% / [[255, 109], [75, 489]], 
* Val   accuracy / confusion: 73.73% / [[152, 78], [77, 283]]

------------------------------ Epoch 300 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.473616
- Iter 028 / 029, Loss: 0.536935

* Train accuracy / confusion: 79.96% / [[257, 104], [82, 485]], 
* Val   accuracy / confusion: 73.73% / [[147, 83], [72, 288]]

------------------------------ Epoch 301 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.432824
- Iter 028 / 029, Loss: 0.538570

* Train accuracy / confusion: 80.06% / [[250, 113], [72, 493]], 
* Val   accuracy / confusion: 73.22% / [[137, 93], [65, 295]]

------------------------------ Epoch 302 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.425786
- Iter 028 / 029, Loss: 0.347920

* Train accuracy / confusion: 79.85% / [[247, 117], [70, 494]], 
* Val   accuracy / confusion: 74.41% / [[142, 88], [63, 297]]

------------------------------ Epoch 303 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.314569
- Iter 028 / 029, Loss: 0.565928

* Train accuracy / confusion: 80.82% / [[256, 106], [72, 494]], 
* Val   accuracy / confusion: 74.41% / [[145, 85], [66, 294]]

------------------------------ Epoch 304 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.387842
- Iter 028 / 029, Loss: 0.334442

* Train accuracy / confusion: 81.14% / [[261, 103], [72, 492]], 
* Val   accuracy / confusion: 73.90% / [[140, 90], [64, 296]]

------------------------------ Epoch 305 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.591995
- Iter 028 / 029, Loss: 0.455837

* Train accuracy / confusion: 80.39% / [[257, 105], [77, 489]], 
* Val   accuracy / confusion: 72.54% / [[126, 104], [58, 302]]

------------------------------ Epoch 306 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.310447
- Iter 028 / 029, Loss: 0.329027

* Train accuracy / confusion: 80.93% / [[262, 103], [74, 489]], 
* Val   accuracy / confusion: 71.02% / [[146, 84], [87, 273]]

------------------------------ Epoch 307 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.459914
- Iter 028 / 029, Loss: 0.380075

* Train accuracy / confusion: 80.17% / [[252, 109], [75, 492]], 
* Val   accuracy / confusion: 74.75% / [[147, 83], [66, 294]]

------------------------------ Epoch 308 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.452803
- Iter 028 / 029, Loss: 0.409771

* Train accuracy / confusion: 82.11% / [[254, 106], [60, 508]], 
* Val   accuracy / confusion: 73.22% / [[141, 89], [69, 291]]

------------------------------ Epoch 309 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.603380
- Iter 028 / 029, Loss: 0.350560

* Train accuracy / confusion: 80.06% / [[255, 109], [76, 488]], 
* Val   accuracy / confusion: 71.86% / [[148, 82], [84, 276]]

------------------------------ Epoch 310 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.429295
- Iter 028 / 029, Loss: 0.469361

* Train accuracy / confusion: 80.06% / [[251, 111], [74, 492]], 
* Val   accuracy / confusion: 73.39% / [[138, 92], [65, 295]]

------------------------------ Epoch 311 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.281730
- Iter 028 / 029, Loss: 0.652853

* Train accuracy / confusion: 79.85% / [[248, 113], [74, 493]], 
* Val   accuracy / confusion: 72.54% / [[134, 96], [66, 294]]

------------------------------ Epoch 312 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.372669
- Iter 028 / 029, Loss: 0.494972

* Train accuracy / confusion: 80.60% / [[250, 110], [70, 498]], 
* Val   accuracy / confusion: 71.19% / [[128, 102], [68, 292]]

------------------------------ Epoch 313 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.414587
- Iter 028 / 029, Loss: 0.338154

* Train accuracy / confusion: 79.96% / [[245, 113], [73, 497]], 
* Val   accuracy / confusion: 72.03% / [[139, 91], [74, 286]]

------------------------------ Epoch 314 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.496476
- Iter 028 / 029, Loss: 0.306083

* Train accuracy / confusion: 79.96% / [[255, 103], [83, 487]], 
* Val   accuracy / confusion: 73.05% / [[142, 88], [71, 289]]

------------------------------ Epoch 315 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.474308
- Iter 028 / 029, Loss: 0.345296

* Train accuracy / confusion: 80.50% / [[252, 109], [72, 495]], 
* Val   accuracy / confusion: 74.07% / [[138, 92], [61, 299]]

------------------------------ Epoch 316 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.252405
- Iter 028 / 029, Loss: 0.391063

* Train accuracy / confusion: 80.93% / [[256, 105], [72, 495]], 
* Val   accuracy / confusion: 73.22% / [[140, 90], [68, 292]]

------------------------------ Epoch 317 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.540062
- Iter 028 / 029, Loss: 0.389162

* Train accuracy / confusion: 80.28% / [[254, 108], [75, 491]], 
* Val   accuracy / confusion: 74.24% / [[138, 92], [60, 300]]

------------------------------ Epoch 318 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.376334
- Iter 028 / 029, Loss: 0.455256

* Train accuracy / confusion: 80.71% / [[252, 112], [67, 497]], 
* Val   accuracy / confusion: 74.07% / [[145, 85], [68, 292]]

------------------------------ Epoch 319 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.607340
- Iter 028 / 029, Loss: 0.541921

* Train accuracy / confusion: 80.39% / [[254, 112], [70, 492]], 
* Val   accuracy / confusion: 72.71% / [[135, 95], [66, 294]]

------------------------------ Epoch 320 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.309544
- Iter 028 / 029, Loss: 0.649951

* Train accuracy / confusion: 80.71% / [[257, 109], [70, 492]], 
* Val   accuracy / confusion: 73.22% / [[149, 81], [77, 283]]

------------------------------ Epoch 321 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.435107
- Iter 028 / 029, Loss: 0.324093

* Train accuracy / confusion: 80.28% / [[245, 116], [67, 500]], 
* Val   accuracy / confusion: 72.71% / [[141, 89], [72, 288]]

------------------------------ Epoch 322 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.297217
- Iter 028 / 029, Loss: 0.564432

* Train accuracy / confusion: 81.47% / [[248, 111], [61, 508]], 
* Val   accuracy / confusion: 73.05% / [[140, 90], [69, 291]]

------------------------------ Epoch 323 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.384585
- Iter 028 / 029, Loss: 0.405099

* Train accuracy / confusion: 79.74% / [[256, 107], [81, 484]], 
* Val   accuracy / confusion: 74.75% / [[138, 92], [57, 303]]

------------------------------ Epoch 324 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.519145
- Iter 028 / 029, Loss: 0.358968

* Train accuracy / confusion: 80.06% / [[257, 103], [82, 486]], 
* Val   accuracy / confusion: 73.22% / [[147, 83], [75, 285]]

------------------------------ Epoch 325 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.477620
- Iter 028 / 029, Loss: 0.569975

* Train accuracy / confusion: 80.93% / [[260, 104], [73, 491]], 
* Val   accuracy / confusion: 74.41% / [[140, 90], [61, 299]]

------------------------------ Epoch 326 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.378435
- Iter 028 / 029, Loss: 0.312897

* Train accuracy / confusion: 80.28% / [[251, 113], [70, 494]], 
* Val   accuracy / confusion: 72.20% / [[136, 94], [70, 290]]

------------------------------ Epoch 327 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.477736
- Iter 028 / 029, Loss: 0.471386

* Train accuracy / confusion: 80.06% / [[259, 102], [83, 484]], 
* Val   accuracy / confusion: 73.22% / [[145, 85], [73, 287]]

------------------------------ Epoch 328 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.567913
- Iter 028 / 029, Loss: 0.510310

* Train accuracy / confusion: 81.14% / [[259, 105], [70, 494]], 
* Val   accuracy / confusion: 74.75% / [[145, 85], [64, 296]]

------------------------------ Epoch 329 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.451940
- Iter 028 / 029, Loss: 0.402486

* Train accuracy / confusion: 81.47% / [[261, 100], [72, 495]], 
* Val   accuracy / confusion: 73.90% / [[153, 77], [77, 283]]

------------------------------ Epoch 330 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.321260
- Iter 028 / 029, Loss: 0.497948

* Train accuracy / confusion: 79.20% / [[239, 120], [73, 496]], 
* Val   accuracy / confusion: 73.73% / [[142, 88], [67, 293]]

------------------------------ Epoch 331 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.407345
- Iter 028 / 029, Loss: 0.523048

* Train accuracy / confusion: 80.17% / [[254, 110], [74, 490]], 
* Val   accuracy / confusion: 73.56% / [[129, 101], [55, 305]]

------------------------------ Epoch 332 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.445758
- Iter 028 / 029, Loss: 0.490692

* Train accuracy / confusion: 80.39% / [[243, 116], [66, 503]], 
* Val   accuracy / confusion: 74.24% / [[137, 93], [59, 301]]

------------------------------ Epoch 333 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.432394
- Iter 028 / 029, Loss: 0.441227

* Train accuracy / confusion: 81.25% / [[250, 112], [62, 504]], 
* Val   accuracy / confusion: 72.20% / [[139, 91], [73, 287]]

------------------------------ Epoch 334 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.386025
- Iter 028 / 029, Loss: 0.375517

* Train accuracy / confusion: 81.36% / [[261, 103], [70, 494]], 
* Val   accuracy / confusion: 72.03% / [[137, 93], [72, 288]]

------------------------------ Epoch 335 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.481276
- Iter 028 / 029, Loss: 0.479307

* Train accuracy / confusion: 81.90% / [[262, 103], [65, 498]], 
* Val   accuracy / confusion: 72.71% / [[137, 93], [68, 292]]

------------------------------ Epoch 336 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.350357
- Iter 028 / 029, Loss: 0.403152

* Train accuracy / confusion: 81.14% / [[258, 106], [69, 495]], 
* Val   accuracy / confusion: 72.88% / [[139, 91], [69, 291]]

------------------------------ Epoch 337 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.351439
- Iter 028 / 029, Loss: 0.418721

* Train accuracy / confusion: 80.28% / [[250, 114], [69, 495]], 
* Val   accuracy / confusion: 73.39% / [[138, 92], [65, 295]]

------------------------------ Epoch 338 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.313096
- Iter 028 / 029, Loss: 0.587852

* Train accuracy / confusion: 82.11% / [[258, 100], [66, 504]], 
* Val   accuracy / confusion: 71.53% / [[142, 88], [80, 280]]

------------------------------ Epoch 339 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.414005
- Iter 028 / 029, Loss: 0.350602

* Train accuracy / confusion: 82.11% / [[259, 96], [70, 503]], 
* Val   accuracy / confusion: 69.83% / [[146, 84], [94, 266]]

------------------------------ Epoch 340 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.609224
- Iter 028 / 029, Loss: 0.275876

* Train accuracy / confusion: 80.39% / [[249, 107], [75, 497]], 
* Val   accuracy / confusion: 75.76% / [[152, 78], [65, 295]]

------------------------------ Epoch 341 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.784430
- Iter 028 / 029, Loss: 0.397234

* Train accuracy / confusion: 79.74% / [[249, 113], [75, 491]], 
* Val   accuracy / confusion: 74.07% / [[138, 92], [61, 299]]

------------------------------ Epoch 342 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.374082
- Iter 028 / 029, Loss: 0.446174

* Train accuracy / confusion: 81.14% / [[256, 106], [69, 497]], 
* Val   accuracy / confusion: 71.69% / [[136, 94], [73, 287]]

------------------------------ Epoch 343 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.411073
- Iter 028 / 029, Loss: 0.343512

* Train accuracy / confusion: 81.47% / [[250, 113], [59, 506]], 
* Val   accuracy / confusion: 75.93% / [[153, 77], [65, 295]]

------------------------------ Epoch 344 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.513998
- Iter 028 / 029, Loss: 0.414002

* Train accuracy / confusion: 80.60% / [[258, 102], [78, 490]], 
* Val   accuracy / confusion: 75.25% / [[148, 82], [64, 296]]

------------------------------ Epoch 345 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.370750
- Iter 028 / 029, Loss: 0.436127

* Train accuracy / confusion: 80.71% / [[256, 106], [73, 493]], 
* Val   accuracy / confusion: 72.54% / [[135, 95], [67, 293]]

------------------------------ Epoch 346 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.465313
- Iter 028 / 029, Loss: 0.638439

* Train accuracy / confusion: 81.25% / [[251, 108], [66, 503]], 
* Val   accuracy / confusion: 74.58% / [[151, 79], [71, 289]]

------------------------------ Epoch 347 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.366289
- Iter 028 / 029, Loss: 0.608990

* Train accuracy / confusion: 79.09% / [[251, 112], [82, 483]], 
* Val   accuracy / confusion: 73.39% / [[145, 85], [72, 288]]

------------------------------ Epoch 348 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.442725
- Iter 028 / 029, Loss: 0.564907

* Train accuracy / confusion: 81.47% / [[264, 99], [73, 492]], 
* Val   accuracy / confusion: 74.07% / [[151, 79], [74, 286]]

------------------------------ Epoch 349 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.306076
- Iter 028 / 029, Loss: 0.372964

* Train accuracy / confusion: 82.33% / [[265, 99], [65, 499]], 
* Val   accuracy / confusion: 72.37% / [[139, 91], [72, 288]]

------------------------------ Epoch 350 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.398925
- Iter 028 / 029, Loss: 0.575495

* Train accuracy / confusion: 81.47% / [[255, 106], [66, 501]], 
* Val   accuracy / confusion: 73.22% / [[133, 97], [61, 299]]

------------------------------ Epoch 351 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.407483
- Iter 028 / 029, Loss: 0.610189

* Train accuracy / confusion: 80.39% / [[246, 114], [68, 500]], 
* Val   accuracy / confusion: 74.75% / [[140, 90], [59, 301]]

------------------------------ Epoch 352 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.399103
- Iter 028 / 029, Loss: 0.396081

* Train accuracy / confusion: 80.82% / [[253, 110], [68, 497]], 
* Val   accuracy / confusion: 73.39% / [[144, 86], [71, 289]]

------------------------------ Epoch 353 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.446373
- Iter 028 / 029, Loss: 0.609170

* Train accuracy / confusion: 80.82% / [[260, 103], [75, 490]], 
* Val   accuracy / confusion: 75.42% / [[139, 91], [54, 306]]

------------------------------ Epoch 354 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.439685
- Iter 028 / 029, Loss: 0.524685

* Train accuracy / confusion: 81.25% / [[256, 106], [68, 498]], 
* Val   accuracy / confusion: 74.24% / [[139, 91], [61, 299]]

------------------------------ Epoch 355 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.324542
- Iter 028 / 029, Loss: 0.312864

* Train accuracy / confusion: 80.82% / [[261, 104], [74, 489]], 
* Val   accuracy / confusion: 74.58% / [[141, 89], [61, 299]]

------------------------------ Epoch 356 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.289350
- Iter 028 / 029, Loss: 0.440722

* Train accuracy / confusion: 80.71% / [[255, 108], [71, 494]], 
* Val   accuracy / confusion: 73.56% / [[147, 83], [73, 287]]

------------------------------ Epoch 357 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.430205
- Iter 028 / 029, Loss: 0.622539

* Train accuracy / confusion: 81.57% / [[259, 102], [69, 498]], 
* Val   accuracy / confusion: 75.42% / [[144, 86], [59, 301]]

------------------------------ Epoch 358 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.392471
- Iter 028 / 029, Loss: 0.448135

* Train accuracy / confusion: 81.47% / [[249, 112], [60, 507]], 
* Val   accuracy / confusion: 73.39% / [[143, 87], [70, 290]]

------------------------------ Epoch 359 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.460306
- Iter 028 / 029, Loss: 0.479533

* Train accuracy / confusion: 81.90% / [[257, 106], [62, 503]], 
* Val   accuracy / confusion: 72.20% / [[132, 98], [66, 294]]

------------------------------ Epoch 360 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.425826
- Iter 028 / 029, Loss: 0.558462

* Train accuracy / confusion: 81.57% / [[257, 101], [70, 500]], 
* Val   accuracy / confusion: 71.53% / [[134, 96], [72, 288]]

------------------------------ Epoch 361 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.416061
- Iter 028 / 029, Loss: 0.401901

* Train accuracy / confusion: 80.39% / [[257, 109], [73, 489]], 
* Val   accuracy / confusion: 72.37% / [[129, 101], [62, 298]]

------------------------------ Epoch 362 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.505103
- Iter 028 / 029, Loss: 0.473280

* Train accuracy / confusion: 80.93% / [[255, 106], [71, 496]], 
* Val   accuracy / confusion: 73.22% / [[135, 95], [63, 297]]

------------------------------ Epoch 363 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.331100
- Iter 028 / 029, Loss: 0.276938

* Train accuracy / confusion: 81.25% / [[253, 107], [67, 501]], 
* Val   accuracy / confusion: 75.25% / [[142, 88], [58, 302]]

------------------------------ Epoch 364 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.516099
- Iter 028 / 029, Loss: 0.368274

* Train accuracy / confusion: 81.36% / [[258, 103], [70, 497]], 
* Val   accuracy / confusion: 74.07% / [[146, 84], [69, 291]]

------------------------------ Epoch 365 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.348175
- Iter 028 / 029, Loss: 0.397396

* Train accuracy / confusion: 81.25% / [[257, 105], [69, 497]], 
* Val   accuracy / confusion: 75.42% / [[148, 82], [63, 297]]

------------------------------ Epoch 366 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.376165
- Iter 028 / 029, Loss: 0.426046

* Train accuracy / confusion: 80.60% / [[259, 103], [77, 489]], 
* Val   accuracy / confusion: 74.07% / [[146, 84], [69, 291]]

------------------------------ Epoch 367 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.340319
- Iter 028 / 029, Loss: 0.352809

* Train accuracy / confusion: 81.03% / [[252, 109], [67, 500]], 
* Val   accuracy / confusion: 72.54% / [[131, 99], [63, 297]]

------------------------------ Epoch 368 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.466375
- Iter 028 / 029, Loss: 0.354616

* Train accuracy / confusion: 80.50% / [[259, 99], [82, 488]], 
* Val   accuracy / confusion: 75.59% / [[153, 77], [67, 293]]

------------------------------ Epoch 369 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.524517
- Iter 028 / 029, Loss: 0.424664

* Train accuracy / confusion: 81.68% / [[264, 101], [69, 494]], 
* Val   accuracy / confusion: 74.58% / [[148, 82], [68, 292]]

------------------------------ Epoch 370 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.502835
- Iter 028 / 029, Loss: 0.332831

* Train accuracy / confusion: 79.96% / [[246, 116], [70, 496]], 
* Val   accuracy / confusion: 74.07% / [[139, 91], [62, 298]]

------------------------------ Epoch 371 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.442894
- Iter 028 / 029, Loss: 0.279792

* Train accuracy / confusion: 80.06% / [[251, 113], [72, 492]], 
* Val   accuracy / confusion: 71.69% / [[123, 107], [60, 300]]

------------------------------ Epoch 372 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.301580
- Iter 028 / 029, Loss: 0.511785

* Train accuracy / confusion: 79.31% / [[247, 113], [79, 489]], 
* Val   accuracy / confusion: 75.08% / [[154, 76], [71, 289]]

------------------------------ Epoch 373 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.463806
- Iter 028 / 029, Loss: 0.498524

* Train accuracy / confusion: 81.03% / [[251, 105], [71, 501]], 
* Val   accuracy / confusion: 72.54% / [[134, 96], [66, 294]]

------------------------------ Epoch 374 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.379429
- Iter 028 / 029, Loss: 0.338456

* Train accuracy / confusion: 81.68% / [[255, 103], [67, 503]], 
* Val   accuracy / confusion: 74.07% / [[156, 74], [79, 281]]

------------------------------ Epoch 375 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.372325
- Iter 028 / 029, Loss: 0.579463

* Train accuracy / confusion: 80.39% / [[253, 108], [74, 493]], 
* Val   accuracy / confusion: 71.53% / [[137, 93], [75, 285]]

------------------------------ Epoch 376 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.357617
- Iter 028 / 029, Loss: 0.288547

* Train accuracy / confusion: 81.36% / [[258, 102], [71, 497]], 
* Val   accuracy / confusion: 74.75% / [[154, 76], [73, 287]]

------------------------------ Epoch 377 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.558527
- Iter 028 / 029, Loss: 0.367416

* Train accuracy / confusion: 81.36% / [[253, 109], [64, 502]], 
* Val   accuracy / confusion: 74.75% / [[148, 82], [67, 293]]

------------------------------ Epoch 378 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.350033
- Iter 028 / 029, Loss: 0.374201

* Train accuracy / confusion: 78.77% / [[245, 116], [81, 486]], 
* Val   accuracy / confusion: 73.39% / [[140, 90], [67, 293]]

------------------------------ Epoch 379 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.451124
- Iter 028 / 029, Loss: 0.321621

* Train accuracy / confusion: 80.60% / [[256, 102], [78, 492]], 
* Val   accuracy / confusion: 75.08% / [[141, 89], [58, 302]]

------------------------------ Epoch 380 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.416704
- Iter 028 / 029, Loss: 0.338862

* Train accuracy / confusion: 82.54% / [[257, 103], [59, 509]], 
* Val   accuracy / confusion: 75.42% / [[145, 85], [60, 300]]

------------------------------ Epoch 381 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.542625
- Iter 028 / 029, Loss: 0.407983

* Train accuracy / confusion: 79.74% / [[258, 106], [82, 482]], 
* Val   accuracy / confusion: 75.93% / [[147, 83], [59, 301]]

------------------------------ Epoch 382 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.365363
- Iter 028 / 029, Loss: 0.583327

* Train accuracy / confusion: 80.82% / [[255, 107], [71, 495]], 
* Val   accuracy / confusion: 74.24% / [[147, 83], [69, 291]]

------------------------------ Epoch 383 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.535809
- Iter 028 / 029, Loss: 0.382510

* Train accuracy / confusion: 81.36% / [[256, 104], [69, 499]], 
* Val   accuracy / confusion: 73.39% / [[142, 88], [69, 291]]

------------------------------ Epoch 384 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.503219
- Iter 028 / 029, Loss: 0.328745

* Train accuracy / confusion: 82.65% / [[268, 91], [70, 499]], 
* Val   accuracy / confusion: 74.58% / [[140, 90], [60, 300]]

------------------------------ Epoch 385 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.393902
- Iter 028 / 029, Loss: 0.460136

* Train accuracy / confusion: 80.71% / [[255, 107], [72, 494]], 
* Val   accuracy / confusion: 73.90% / [[148, 82], [72, 288]]

------------------------------ Epoch 386 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.477231
- Iter 028 / 029, Loss: 0.386878

* Train accuracy / confusion: 82.44% / [[259, 100], [63, 506]], 
* Val   accuracy / confusion: 72.88% / [[134, 96], [64, 296]]

------------------------------ Epoch 387 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.467829
- Iter 028 / 029, Loss: 0.614416

* Train accuracy / confusion: 80.50% / [[256, 106], [75, 491]], 
* Val   accuracy / confusion: 71.86% / [[128, 102], [64, 296]]

------------------------------ Epoch 388 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.346433
- Iter 028 / 029, Loss: 0.397111

* Train accuracy / confusion: 79.85% / [[252, 110], [77, 489]], 
* Val   accuracy / confusion: 73.39% / [[141, 89], [68, 292]]

------------------------------ Epoch 389 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.292440
- Iter 028 / 029, Loss: 0.477571

* Train accuracy / confusion: 81.79% / [[264, 99], [70, 495]], 
* Val   accuracy / confusion: 74.07% / [[146, 84], [69, 291]]

------------------------------ Epoch 390 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.464633
- Iter 028 / 029, Loss: 0.588122

* Train accuracy / confusion: 82.00% / [[259, 102], [65, 502]], 
* Val   accuracy / confusion: 74.41% / [[129, 101], [50, 310]]

------------------------------ Epoch 391 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.426506
- Iter 028 / 029, Loss: 0.609985

* Train accuracy / confusion: 81.36% / [[259, 106], [67, 496]], 
* Val   accuracy / confusion: 73.56% / [[148, 82], [74, 286]]

------------------------------ Epoch 392 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.516662
- Iter 028 / 029, Loss: 0.351355

* Train accuracy / confusion: 82.11% / [[264, 97], [69, 498]], 
* Val   accuracy / confusion: 72.88% / [[144, 86], [74, 286]]

------------------------------ Epoch 393 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.274696
- Iter 028 / 029, Loss: 0.470040

* Train accuracy / confusion: 82.44% / [[267, 95], [68, 498]], 
* Val   accuracy / confusion: 73.56% / [[156, 74], [82, 278]]

------------------------------ Epoch 394 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.370194
- Iter 028 / 029, Loss: 0.430226

* Train accuracy / confusion: 81.14% / [[254, 107], [68, 499]], 
* Val   accuracy / confusion: 74.92% / [[150, 80], [68, 292]]

------------------------------ Epoch 395 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.461928
- Iter 028 / 029, Loss: 0.470170

* Train accuracy / confusion: 80.82% / [[260, 99], [79, 490]], 
* Val   accuracy / confusion: 74.07% / [[134, 96], [57, 303]]

------------------------------ Epoch 396 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.362884
- Iter 028 / 029, Loss: 0.407856

* Train accuracy / confusion: 82.00% / [[261, 104], [63, 500]], 
* Val   accuracy / confusion: 72.88% / [[129, 101], [59, 301]]

------------------------------ Epoch 397 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.275957
- Iter 028 / 029, Loss: 0.355648

* Train accuracy / confusion: 80.50% / [[257, 105], [76, 490]], 
* Val   accuracy / confusion: 73.90% / [[142, 88], [66, 294]]

------------------------------ Epoch 398 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.416651
- Iter 028 / 029, Loss: 0.312933

* Train accuracy / confusion: 80.28% / [[256, 107], [76, 489]], 
* Val   accuracy / confusion: 73.22% / [[136, 94], [64, 296]]

------------------------------ Epoch 399 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.380822
- Iter 028 / 029, Loss: 0.511717

* Train accuracy / confusion: 80.82% / [[254, 109], [69, 496]], 
* Val   accuracy / confusion: 74.07% / [[131, 99], [54, 306]]

------------------------------ Epoch 400 / 500, Learning rate: 1.92e-04 ------------------------------
- Iter 014 / 029, Loss: 0.382955
- Iter 028 / 029, Loss: 0.348450

* Train accuracy / confusion: 81.79% / [[261, 98], [71, 498]], 
* Val   accuracy / confusion: 75.25% / [[152, 78], [68, 292]]

------------------------------ Epoch 401 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.336350
- Iter 028 / 029, Loss: 0.370183

* Train accuracy / confusion: 82.11% / [[258, 102], [64, 504]], 
* Val   accuracy / confusion: 74.75% / [[148, 82], [67, 293]]

------------------------------ Epoch 402 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.421328
- Iter 028 / 029, Loss: 0.406207

* Train accuracy / confusion: 79.85% / [[250, 114], [73, 491]], 
* Val   accuracy / confusion: 73.22% / [[139, 91], [67, 293]]

------------------------------ Epoch 403 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.452431
- Iter 028 / 029, Loss: 0.476947

* Train accuracy / confusion: 81.14% / [[255, 110], [65, 498]], 
* Val   accuracy / confusion: 73.56% / [[145, 85], [71, 289]]

------------------------------ Epoch 404 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.553239
- Iter 028 / 029, Loss: 0.528363

* Train accuracy / confusion: 82.33% / [[256, 108], [56, 508]], 
* Val   accuracy / confusion: 74.58% / [[138, 92], [58, 302]]

------------------------------ Epoch 405 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.574160
- Iter 028 / 029, Loss: 0.336401

* Train accuracy / confusion: 80.82% / [[250, 109], [69, 500]], 
* Val   accuracy / confusion: 75.08% / [[144, 86], [61, 299]]

------------------------------ Epoch 406 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.308610
- Iter 028 / 029, Loss: 0.328319

* Train accuracy / confusion: 80.71% / [[251, 106], [73, 498]], 
* Val   accuracy / confusion: 72.37% / [[149, 81], [82, 278]]

------------------------------ Epoch 407 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.328367
- Iter 028 / 029, Loss: 0.485884

* Train accuracy / confusion: 82.00% / [[257, 104], [63, 504]], 
* Val   accuracy / confusion: 70.68% / [[139, 91], [82, 278]]

------------------------------ Epoch 408 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.433647
- Iter 028 / 029, Loss: 0.380590

* Train accuracy / confusion: 80.93% / [[261, 104], [73, 490]], 
* Val   accuracy / confusion: 72.71% / [[133, 97], [64, 296]]

------------------------------ Epoch 409 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.507181
- Iter 028 / 029, Loss: 0.277618

* Train accuracy / confusion: 82.76% / [[262, 100], [60, 506]], 
* Val   accuracy / confusion: 73.39% / [[141, 89], [68, 292]]

------------------------------ Epoch 410 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.339507
- Iter 028 / 029, Loss: 0.508032

* Train accuracy / confusion: 80.71% / [[252, 108], [71, 497]], 
* Val   accuracy / confusion: 74.41% / [[141, 89], [62, 298]]

------------------------------ Epoch 411 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.407391
- Iter 028 / 029, Loss: 0.295338

* Train accuracy / confusion: 79.42% / [[252, 109], [82, 485]], 
* Val   accuracy / confusion: 73.22% / [[139, 91], [67, 293]]

------------------------------ Epoch 412 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.467534
- Iter 028 / 029, Loss: 0.370917

* Train accuracy / confusion: 80.17% / [[254, 109], [75, 490]], 
* Val   accuracy / confusion: 74.07% / [[137, 93], [60, 300]]

------------------------------ Epoch 413 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.412239
- Iter 028 / 029, Loss: 0.341872

* Train accuracy / confusion: 82.33% / [[271, 94], [70, 493]], 
* Val   accuracy / confusion: 74.07% / [[142, 88], [65, 295]]

------------------------------ Epoch 414 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.353238
- Iter 028 / 029, Loss: 0.410597

* Train accuracy / confusion: 81.90% / [[253, 107], [61, 507]], 
* Val   accuracy / confusion: 73.73% / [[146, 84], [71, 289]]

------------------------------ Epoch 415 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.437701
- Iter 028 / 029, Loss: 0.457419

* Train accuracy / confusion: 81.47% / [[260, 101], [71, 496]], 
* Val   accuracy / confusion: 73.22% / [[137, 93], [65, 295]]

------------------------------ Epoch 416 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.439833
- Iter 028 / 029, Loss: 0.399539

* Train accuracy / confusion: 79.53% / [[254, 104], [86, 484]], 
* Val   accuracy / confusion: 75.25% / [[144, 86], [60, 300]]

------------------------------ Epoch 417 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.293895
- Iter 028 / 029, Loss: 0.332623

* Train accuracy / confusion: 80.28% / [[254, 109], [74, 491]], 
* Val   accuracy / confusion: 73.39% / [[145, 85], [72, 288]]

------------------------------ Epoch 418 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.364197
- Iter 028 / 029, Loss: 0.421522

* Train accuracy / confusion: 80.60% / [[249, 109], [71, 499]], 
* Val   accuracy / confusion: 73.05% / [[143, 87], [72, 288]]

------------------------------ Epoch 419 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.439089
- Iter 028 / 029, Loss: 0.490299

* Train accuracy / confusion: 81.03% / [[257, 106], [70, 495]], 
* Val   accuracy / confusion: 74.07% / [[141, 89], [64, 296]]

------------------------------ Epoch 420 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.582698
- Iter 028 / 029, Loss: 0.519990

* Train accuracy / confusion: 80.82% / [[259, 102], [76, 491]], 
* Val   accuracy / confusion: 72.54% / [[136, 94], [68, 292]]

------------------------------ Epoch 421 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.334754
- Iter 028 / 029, Loss: 0.435656

* Train accuracy / confusion: 81.47% / [[262, 103], [69, 494]], 
* Val   accuracy / confusion: 74.75% / [[140, 90], [59, 301]]

------------------------------ Epoch 422 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.447568
- Iter 028 / 029, Loss: 0.300743

* Train accuracy / confusion: 82.44% / [[265, 97], [66, 500]], 
* Val   accuracy / confusion: 73.56% / [[142, 88], [68, 292]]

------------------------------ Epoch 423 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.607249
- Iter 028 / 029, Loss: 0.550496

* Train accuracy / confusion: 80.39% / [[252, 108], [74, 494]], 
* Val   accuracy / confusion: 74.07% / [[151, 79], [74, 286]]

------------------------------ Epoch 424 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.439514
- Iter 028 / 029, Loss: 0.383287

* Train accuracy / confusion: 80.39% / [[250, 116], [66, 496]], 
* Val   accuracy / confusion: 75.59% / [[153, 77], [67, 293]]

------------------------------ Epoch 425 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.337423
- Iter 028 / 029, Loss: 0.395575

* Train accuracy / confusion: 81.36% / [[262, 103], [70, 493]], 
* Val   accuracy / confusion: 73.39% / [[148, 82], [75, 285]]

------------------------------ Epoch 426 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.272637
- Iter 028 / 029, Loss: 0.256054

* Train accuracy / confusion: 80.93% / [[257, 107], [70, 494]], 
* Val   accuracy / confusion: 74.75% / [[138, 92], [57, 303]]

------------------------------ Epoch 427 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.507362
- Iter 028 / 029, Loss: 0.563015

* Train accuracy / confusion: 83.30% / [[268, 94], [61, 505]], 
* Val   accuracy / confusion: 74.24% / [[142, 88], [64, 296]]

------------------------------ Epoch 428 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.469850
- Iter 028 / 029, Loss: 0.637719

* Train accuracy / confusion: 80.39% / [[263, 101], [81, 483]], 
* Val   accuracy / confusion: 75.59% / [[149, 81], [63, 297]]

------------------------------ Epoch 429 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.519848
- Iter 028 / 029, Loss: 0.358673

* Train accuracy / confusion: 82.54% / [[260, 103], [59, 506]], 
* Val   accuracy / confusion: 74.41% / [[144, 86], [65, 295]]

------------------------------ Epoch 430 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.463943
- Iter 028 / 029, Loss: 0.400720

* Train accuracy / confusion: 79.85% / [[251, 111], [76, 490]], 
* Val   accuracy / confusion: 72.88% / [[134, 96], [64, 296]]

------------------------------ Epoch 431 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.518387
- Iter 028 / 029, Loss: 0.626717

* Train accuracy / confusion: 80.50% / [[247, 114], [67, 500]], 
* Val   accuracy / confusion: 75.25% / [[147, 83], [63, 297]]

------------------------------ Epoch 432 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.498379
- Iter 028 / 029, Loss: 0.278479

* Train accuracy / confusion: 81.79% / [[263, 97], [72, 496]], 
* Val   accuracy / confusion: 75.08% / [[144, 86], [61, 299]]

------------------------------ Epoch 433 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.349040
- Iter 028 / 029, Loss: 0.350075

* Train accuracy / confusion: 81.36% / [[259, 104], [69, 496]], 
* Val   accuracy / confusion: 73.73% / [[135, 95], [60, 300]]

------------------------------ Epoch 434 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.358778
- Iter 028 / 029, Loss: 0.436202

* Train accuracy / confusion: 81.68% / [[265, 98], [72, 493]], 
* Val   accuracy / confusion: 73.05% / [[135, 95], [64, 296]]

------------------------------ Epoch 435 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.461162
- Iter 028 / 029, Loss: 0.554700

* Train accuracy / confusion: 80.06% / [[256, 106], [79, 487]], 
* Val   accuracy / confusion: 75.08% / [[150, 80], [67, 293]]

------------------------------ Epoch 436 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.532302
- Iter 028 / 029, Loss: 0.395501

* Train accuracy / confusion: 81.36% / [[263, 96], [77, 492]], 
* Val   accuracy / confusion: 72.88% / [[142, 88], [72, 288]]

------------------------------ Epoch 437 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.377444
- Iter 028 / 029, Loss: 0.353891

* Train accuracy / confusion: 81.57% / [[263, 98], [73, 494]], 
* Val   accuracy / confusion: 73.73% / [[147, 83], [72, 288]]

------------------------------ Epoch 438 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.367616
- Iter 028 / 029, Loss: 0.539807

* Train accuracy / confusion: 82.65% / [[267, 93], [68, 500]], 
* Val   accuracy / confusion: 73.39% / [[138, 92], [65, 295]]

------------------------------ Epoch 439 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.402374
- Iter 028 / 029, Loss: 0.523535

* Train accuracy / confusion: 80.60% / [[255, 106], [74, 493]], 
* Val   accuracy / confusion: 74.24% / [[143, 87], [65, 295]]

------------------------------ Epoch 440 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.300559
- Iter 028 / 029, Loss: 0.452561

* Train accuracy / confusion: 81.47% / [[260, 104], [68, 496]], 
* Val   accuracy / confusion: 71.69% / [[129, 101], [66, 294]]

------------------------------ Epoch 441 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.342821
- Iter 028 / 029, Loss: 0.516409

* Train accuracy / confusion: 82.33% / [[259, 104], [60, 505]], 
* Val   accuracy / confusion: 75.42% / [[147, 83], [62, 298]]

------------------------------ Epoch 442 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.478125
- Iter 028 / 029, Loss: 0.426852

* Train accuracy / confusion: 80.71% / [[256, 104], [75, 493]], 
* Val   accuracy / confusion: 72.88% / [[141, 89], [71, 289]]

------------------------------ Epoch 443 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.478191
- Iter 028 / 029, Loss: 0.470948

* Train accuracy / confusion: 80.60% / [[258, 106], [74, 490]], 
* Val   accuracy / confusion: 75.42% / [[138, 92], [53, 307]]

------------------------------ Epoch 444 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.607628
- Iter 028 / 029, Loss: 0.433143

* Train accuracy / confusion: 81.36% / [[259, 106], [67, 496]], 
* Val   accuracy / confusion: 74.92% / [[139, 91], [57, 303]]

------------------------------ Epoch 445 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.284105
- Iter 028 / 029, Loss: 0.552317

* Train accuracy / confusion: 82.33% / [[262, 102], [62, 502]], 
* Val   accuracy / confusion: 74.24% / [[151, 79], [73, 287]]

------------------------------ Epoch 446 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.461810
- Iter 028 / 029, Loss: 0.444652

* Train accuracy / confusion: 81.90% / [[267, 96], [72, 493]], 
* Val   accuracy / confusion: 72.71% / [[142, 88], [73, 287]]

------------------------------ Epoch 447 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.467007
- Iter 028 / 029, Loss: 0.395242

* Train accuracy / confusion: 81.68% / [[254, 106], [64, 504]], 
* Val   accuracy / confusion: 74.07% / [[146, 84], [69, 291]]

------------------------------ Epoch 448 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.547088
- Iter 028 / 029, Loss: 0.442753

* Train accuracy / confusion: 82.00% / [[260, 99], [68, 501]], 
* Val   accuracy / confusion: 75.08% / [[142, 88], [59, 301]]

------------------------------ Epoch 449 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.335604
- Iter 028 / 029, Loss: 0.359518

* Train accuracy / confusion: 81.90% / [[262, 98], [70, 498]], 
* Val   accuracy / confusion: 73.39% / [[138, 92], [65, 295]]

------------------------------ Epoch 450 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.375072
- Iter 028 / 029, Loss: 0.583866

* Train accuracy / confusion: 81.25% / [[254, 109], [65, 500]], 
* Val   accuracy / confusion: 73.22% / [[142, 88], [70, 290]]

------------------------------ Epoch 451 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.287089
- Iter 028 / 029, Loss: 0.521236

* Train accuracy / confusion: 82.22% / [[259, 102], [63, 504]], 
* Val   accuracy / confusion: 73.22% / [[139, 91], [67, 293]]

------------------------------ Epoch 452 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.536013
- Iter 028 / 029, Loss: 0.383194

* Train accuracy / confusion: 82.44% / [[270, 94], [69, 495]], 
* Val   accuracy / confusion: 74.58% / [[146, 84], [66, 294]]

------------------------------ Epoch 453 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.460353
- Iter 028 / 029, Loss: 0.251847

* Train accuracy / confusion: 81.90% / [[255, 104], [64, 505]], 
* Val   accuracy / confusion: 73.22% / [[140, 90], [68, 292]]

------------------------------ Epoch 454 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.418830
- Iter 028 / 029, Loss: 0.433185

* Train accuracy / confusion: 81.68% / [[256, 103], [67, 502]], 
* Val   accuracy / confusion: 72.88% / [[134, 96], [64, 296]]

------------------------------ Epoch 455 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.566999
- Iter 028 / 029, Loss: 0.549452

* Train accuracy / confusion: 82.44% / [[259, 105], [58, 506]], 
* Val   accuracy / confusion: 75.25% / [[144, 86], [60, 300]]

------------------------------ Epoch 456 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.412785
- Iter 028 / 029, Loss: 0.329301

* Train accuracy / confusion: 82.65% / [[268, 97], [64, 499]], 
* Val   accuracy / confusion: 71.86% / [[141, 89], [77, 283]]

------------------------------ Epoch 457 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.384275
- Iter 028 / 029, Loss: 0.451561

* Train accuracy / confusion: 81.79% / [[264, 99], [70, 495]], 
* Val   accuracy / confusion: 74.41% / [[150, 80], [71, 289]]

------------------------------ Epoch 458 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.345960
- Iter 028 / 029, Loss: 0.584815

* Train accuracy / confusion: 81.14% / [[256, 109], [66, 497]], 
* Val   accuracy / confusion: 73.39% / [[144, 86], [71, 289]]

------------------------------ Epoch 459 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.499513
- Iter 028 / 029, Loss: 0.422954

* Train accuracy / confusion: 80.17% / [[254, 105], [79, 490]], 
* Val   accuracy / confusion: 73.05% / [[140, 90], [69, 291]]

------------------------------ Epoch 460 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.308054
- Iter 028 / 029, Loss: 0.549424

* Train accuracy / confusion: 82.33% / [[258, 107], [57, 506]], 
* Val   accuracy / confusion: 75.42% / [[149, 81], [64, 296]]

------------------------------ Epoch 461 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.346429
- Iter 028 / 029, Loss: 0.510089

* Train accuracy / confusion: 81.68% / [[263, 99], [71, 495]], 
* Val   accuracy / confusion: 73.90% / [[142, 88], [66, 294]]

------------------------------ Epoch 462 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.349402
- Iter 028 / 029, Loss: 0.390361

* Train accuracy / confusion: 80.60% / [[258, 105], [75, 490]], 
* Val   accuracy / confusion: 74.75% / [[148, 82], [67, 293]]

------------------------------ Epoch 463 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.422630
- Iter 028 / 029, Loss: 0.537317

* Train accuracy / confusion: 81.36% / [[262, 103], [70, 493]], 
* Val   accuracy / confusion: 75.08% / [[144, 86], [61, 299]]

------------------------------ Epoch 464 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.333863
- Iter 028 / 029, Loss: 0.406973

* Train accuracy / confusion: 81.36% / [[261, 105], [68, 494]], 
* Val   accuracy / confusion: 73.73% / [[132, 98], [57, 303]]

------------------------------ Epoch 465 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.425729
- Iter 028 / 029, Loss: 0.511397

* Train accuracy / confusion: 80.17% / [[252, 112], [72, 492]], 
* Val   accuracy / confusion: 72.37% / [[141, 89], [74, 286]]

------------------------------ Epoch 466 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.435593
- Iter 028 / 029, Loss: 0.391072

* Train accuracy / confusion: 81.57% / [[259, 102], [69, 498]], 
* Val   accuracy / confusion: 74.24% / [[144, 86], [66, 294]]

------------------------------ Epoch 467 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.395049
- Iter 028 / 029, Loss: 0.388452

* Train accuracy / confusion: 81.68% / [[260, 99], [71, 498]], 
* Val   accuracy / confusion: 73.39% / [[144, 86], [71, 289]]

------------------------------ Epoch 468 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.369386
- Iter 028 / 029, Loss: 0.490195

* Train accuracy / confusion: 80.39% / [[258, 108], [74, 488]], 
* Val   accuracy / confusion: 73.22% / [[141, 89], [69, 291]]

------------------------------ Epoch 469 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.313237
- Iter 028 / 029, Loss: 0.482751

* Train accuracy / confusion: 81.79% / [[260, 103], [66, 499]], 
* Val   accuracy / confusion: 73.05% / [[141, 89], [70, 290]]

------------------------------ Epoch 470 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.345183
- Iter 028 / 029, Loss: 0.521277

* Train accuracy / confusion: 80.93% / [[258, 102], [75, 493]], 
* Val   accuracy / confusion: 71.86% / [[141, 89], [77, 283]]

------------------------------ Epoch 471 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.466116
- Iter 028 / 029, Loss: 0.498724

* Train accuracy / confusion: 82.54% / [[268, 95], [67, 498]], 
* Val   accuracy / confusion: 75.59% / [[147, 83], [61, 299]]

------------------------------ Epoch 472 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.323219
- Iter 028 / 029, Loss: 0.386375

* Train accuracy / confusion: 81.79% / [[257, 102], [67, 502]], 
* Val   accuracy / confusion: 73.73% / [[140, 90], [65, 295]]

------------------------------ Epoch 473 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.373600
- Iter 028 / 029, Loss: 0.352128

* Train accuracy / confusion: 80.17% / [[252, 109], [75, 492]], 
* Val   accuracy / confusion: 74.07% / [[154, 76], [77, 283]]

------------------------------ Epoch 474 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.700005
- Iter 028 / 029, Loss: 0.517180

* Train accuracy / confusion: 80.71% / [[257, 108], [71, 492]], 
* Val   accuracy / confusion: 73.22% / [[136, 94], [64, 296]]

------------------------------ Epoch 475 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.366180
- Iter 028 / 029, Loss: 0.390655

* Train accuracy / confusion: 81.68% / [[261, 102], [68, 497]], 
* Val   accuracy / confusion: 74.75% / [[146, 84], [65, 295]]

------------------------------ Epoch 476 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.336024
- Iter 028 / 029, Loss: 0.419590

* Train accuracy / confusion: 79.85% / [[250, 113], [74, 491]], 
* Val   accuracy / confusion: 73.22% / [[140, 90], [68, 292]]

------------------------------ Epoch 477 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.397156
- Iter 028 / 029, Loss: 0.434994

* Train accuracy / confusion: 81.68% / [[258, 102], [68, 500]], 
* Val   accuracy / confusion: 73.05% / [[143, 87], [72, 288]]

------------------------------ Epoch 478 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.481219
- Iter 028 / 029, Loss: 0.530384

* Train accuracy / confusion: 81.68% / [[260, 102], [68, 498]], 
* Val   accuracy / confusion: 73.39% / [[139, 91], [66, 294]]

------------------------------ Epoch 479 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.405363
- Iter 028 / 029, Loss: 0.441619

* Train accuracy / confusion: 81.68% / [[259, 101], [69, 499]], 
* Val   accuracy / confusion: 74.07% / [[146, 84], [69, 291]]

------------------------------ Epoch 480 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.595391
- Iter 028 / 029, Loss: 0.438990

* Train accuracy / confusion: 82.33% / [[269, 93], [71, 495]], 
* Val   accuracy / confusion: 71.69% / [[137, 93], [74, 286]]

------------------------------ Epoch 481 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.509994
- Iter 028 / 029, Loss: 0.484202

* Train accuracy / confusion: 81.03% / [[259, 105], [71, 493]], 
* Val   accuracy / confusion: 74.41% / [[155, 75], [76, 284]]

------------------------------ Epoch 482 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.314125
- Iter 028 / 029, Loss: 0.421702

* Train accuracy / confusion: 82.65% / [[266, 98], [63, 501]], 
* Val   accuracy / confusion: 73.05% / [[137, 93], [66, 294]]

------------------------------ Epoch 483 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.510541
- Iter 028 / 029, Loss: 0.459117

* Train accuracy / confusion: 81.03% / [[251, 113], [63, 501]], 
* Val   accuracy / confusion: 72.37% / [[135, 95], [68, 292]]

------------------------------ Epoch 484 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.329436
- Iter 028 / 029, Loss: 0.284477

* Train accuracy / confusion: 80.39% / [[257, 106], [76, 489]], 
* Val   accuracy / confusion: 74.75% / [[138, 92], [57, 303]]

------------------------------ Epoch 485 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.284713
- Iter 028 / 029, Loss: 0.396584

* Train accuracy / confusion: 82.44% / [[260, 100], [63, 505]], 
* Val   accuracy / confusion: 71.86% / [[139, 91], [75, 285]]

------------------------------ Epoch 486 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.396515
- Iter 028 / 029, Loss: 0.339656

* Train accuracy / confusion: 80.82% / [[264, 99], [79, 486]], 
* Val   accuracy / confusion: 72.71% / [[144, 86], [75, 285]]

------------------------------ Epoch 487 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.462090
- Iter 028 / 029, Loss: 0.410743

* Train accuracy / confusion: 81.36% / [[258, 102], [71, 497]], 
* Val   accuracy / confusion: 72.88% / [[136, 94], [66, 294]]

------------------------------ Epoch 488 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.390172
- Iter 028 / 029, Loss: 0.432072

* Train accuracy / confusion: 81.14% / [[250, 106], [69, 503]], 
* Val   accuracy / confusion: 75.42% / [[152, 78], [67, 293]]

------------------------------ Epoch 489 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.533423
- Iter 028 / 029, Loss: 0.347568

* Train accuracy / confusion: 81.47% / [[261, 103], [69, 495]], 
* Val   accuracy / confusion: 71.86% / [[140, 90], [76, 284]]

------------------------------ Epoch 490 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.373709
- Iter 028 / 029, Loss: 0.352697

* Train accuracy / confusion: 81.57% / [[261, 101], [70, 496]], 
* Val   accuracy / confusion: 74.92% / [[141, 89], [59, 301]]

------------------------------ Epoch 491 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.453348
- Iter 028 / 029, Loss: 0.510906

* Train accuracy / confusion: 81.14% / [[256, 108], [67, 497]], 
* Val   accuracy / confusion: 73.56% / [[142, 88], [68, 292]]

------------------------------ Epoch 492 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.386341
- Iter 028 / 029, Loss: 0.270880

* Train accuracy / confusion: 81.03% / [[252, 111], [65, 500]], 
* Val   accuracy / confusion: 73.56% / [[151, 79], [77, 283]]

------------------------------ Epoch 493 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.388330
- Iter 028 / 029, Loss: 0.471641

* Train accuracy / confusion: 80.50% / [[260, 104], [77, 487]], 
* Val   accuracy / confusion: 72.54% / [[140, 90], [72, 288]]

------------------------------ Epoch 494 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.405912
- Iter 028 / 029, Loss: 0.350936

* Train accuracy / confusion: 80.82% / [[261, 98], [80, 489]], 
* Val   accuracy / confusion: 73.73% / [[147, 83], [72, 288]]

------------------------------ Epoch 495 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.400960
- Iter 028 / 029, Loss: 0.515517

* Train accuracy / confusion: 79.53% / [[247, 116], [74, 491]], 
* Val   accuracy / confusion: 72.20% / [[134, 96], [68, 292]]

------------------------------ Epoch 496 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.437835
- Iter 028 / 029, Loss: 0.395255

* Train accuracy / confusion: 80.82% / [[258, 103], [75, 492]], 
* Val   accuracy / confusion: 72.54% / [[142, 88], [74, 286]]

------------------------------ Epoch 497 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.454821
- Iter 028 / 029, Loss: 0.263715

* Train accuracy / confusion: 82.65% / [[255, 105], [56, 512]], 
* Val   accuracy / confusion: 75.08% / [[143, 87], [60, 300]]

------------------------------ Epoch 498 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.245078
- Iter 028 / 029, Loss: 0.565779

* Train accuracy / confusion: 81.90% / [[257, 102], [66, 503]], 
* Val   accuracy / confusion: 72.20% / [[139, 91], [73, 287]]

------------------------------ Epoch 499 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.447749
- Iter 028 / 029, Loss: 0.604006

* Train accuracy / confusion: 81.47% / [[259, 103], [69, 497]], 
* Val   accuracy / confusion: 74.07% / [[141, 89], [64, 296]]

------------------------------ Epoch 500 / 500, Learning rate: 1.92e-05 ------------------------------
- Iter 014 / 029, Loss: 0.507714
- Iter 028 / 029, Loss: 0.483399

* Train accuracy / confusion: 80.06% / [[258, 107], [78, 485]], 
* Val   accuracy / confusion: 73.05% / [[140, 90], [69, 291]]

**************************************** Training Ends ****************************************

- Test accuracy (last model): 73.03%
- Confusion matrix (last model):
 [[ 897  513]
 [ 458 1732]]

- Test accuracy (best model): 73.03%
- Confusion matrix (best model):
 [[ 779  631]
 [ 340 1850]]

# checkpoint save path
if save_checkpoint:
    os.makedirs('checkpoint/', exist_ok=True)
    today = datetime.date.today()
    torch.save(best_model_state, f'checkpoint/{today.year % 100}{today.month:02d}{today.day}_{nb_fname}_M5_best')
    torch.save(last_model_state, f'checkpoint/{today.year % 100}{today.month:02d}{today.day}_{nb_fname}_M5_last')

print('- Debug table:')
pprint.pp(last_test_debug, indent=2, width=100)

- Debug table:
{ '01183': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01303198_020317'},
  '00697': {'GT': 0, 'Acc': '  0.00%', 'Pred': [0, 30], 'edfname': '00983533_290618'},
  '00825': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01129445_130220'},
  '00504': {'GT': 0, 'Acc': '  0.00%', 'Pred': [0, 30], 'edfname': '00813343_041218'},
  '00192': {'GT': 0, 'Acc': '  0.00%', 'Pred': [0, 30], 'edfname': '00608961_131118'},
  '00134': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '00446328_171116'},
  '00741': {'GT': 0, 'Acc': ' 20.00%', 'Pred': [6, 24], 'edfname': '01025734_280715'},
  '00206': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00616193_090218'},
  '01231': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01334787_211117'},
  '00793': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01086373_020615'},
  '01045': {'GT': 0, 'Acc': ' 90.00%', 'Pred': [27, 3], 'edfname': '01235281_191015'},
  '00407': {'GT': 1, 'Acc': ' 70.00%', 'Pred': [9, 21], 'edfname': '00740694_110315'},
  '00669': {'GT': 1, 'Acc': '  0.00%', 'Pred': [30, 0], 'edfname': '00957862_230317'},
  '00843': {'GT': 1, 'Acc': '  0.00%', 'Pred': [30, 0], 'edfname': '01135545_230715'},
  '00029': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00164098_180919'},
  '00299': {'GT': 0, 'Acc': '  0.00%', 'Pred': [0, 30], 'edfname': '00671212_160819'},
  '00702': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00985987_180518'},
  '01069': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01243158_301115'},
  '00913': {'GT': 0, 'Acc': ' 80.00%', 'Pred': [24, 6], 'edfname': '01151967_160414'},
  '01307': {'GT': 0, 'Acc': '  0.00%', 'Pred': [0, 30], 'edfname': '01376302_060718'},
  '00638': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00941649_111218'},
  '00286': {'GT': 1, 'Acc': ' 13.33%', 'Pred': [26, 4], 'edfname': '00663561_030414'},
  '00954': {'GT': 1, 'Acc': ' 56.67%', 'Pred': [13, 17], 'edfname': '01178797_240914'},
  '00587': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00894185_250817'},
  '00542': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '00852650_170818'},
  '00996': {'GT': 1, 'Acc': ' 80.00%', 'Pred': [6, 24], 'edfname': '01204692_120315'},
  '00403': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00739162_011215'},
  '00408': {'GT': 0, 'Acc': ' 13.33%', 'Pred': [4, 26], 'edfname': '00740750_110315'},
  '00078': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00324958_271118'},
  '00277': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00657017_281218'},
  '00671': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00958455_200917'},
  '01066': {'GT': 0, 'Acc': ' 76.67%', 'Pred': [23, 7], 'edfname': '01242983_071215'},
  '00965': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01186214'},
  '01125': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01276737_300616'},
  '00227': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00626957_071217'},
  '00531': {'GT': 0, 'Acc': ' 73.33%', 'Pred': [22, 8], 'edfname': '00840844_250119'},
  '00088': {'GT': 1, 'Acc': ' 53.33%', 'Pred': [14, 16], 'edfname': '00344923_021116'},
  '00267': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '00650465_160318'},
  '00069': {'GT': 1, 'Acc': ' 86.67%', 'Pred': [4, 26], 'edfname': '00307906_230617'},
  '00365': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00712852_060418'},
  '00991': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01203444_090819'},
  '00815': {'GT': 0, 'Acc': ' 70.00%', 'Pred': [21, 9], 'edfname': '01125477_030918'},
  '01351': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01409497_111219'},
  '00065': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00293228_070918'},
  '00952': {'GT': 1, 'Acc': ' 53.33%', 'Pred': [14, 16], 'edfname': '01178672_300518'},
  '00124': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00418981_060116'},
  '00854': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01138301_230114'},
  '00472': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00784418_201016'},
  '01258': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01348039_181017'},
  '01375': {'GT': 1, 'Acc': ' 56.67%', 'Pred': [13, 17], 'edfname': '01429374_230519'},
  '00885': {'GT': 0, 'Acc': ' 30.00%', 'Pred': [9, 21], 'edfname': '01142810_180214'},
  '00917': {'GT': 0, 'Acc': ' 13.33%', 'Pred': [4, 26], 'edfname': '01154159_230414'},
  '00938': {'GT': 0, 'Acc': '  0.00%', 'Pred': [0, 30], 'edfname': '01161826_050916'},
  '00881': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01141790_190214'},
  '00096': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00369252_131216'},
  '01075': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01250004_260116'},
  '01165': {'GT': 0, 'Acc': ' 43.33%', 'Pred': [13, 17], 'edfname': '01296533_281116'},
  '01067': {'GT': 1, 'Acc': '  0.00%', 'Pred': [30, 0], 'edfname': '01242984_211215'},
  '00828': {'GT': 1, 'Acc': ' 90.00%', 'Pred': [3, 27], 'edfname': '01131959_310118'},
  '01337': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01400560_160419'},
  '00383': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00723110_240419'},
  '00900': {'GT': 0, 'Acc': '  3.33%', 'Pred': [1, 29], 'edfname': '01147100'},
  '01336': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '01398060_050918'},
  '01115': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01271298_270319'},
  '00667': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00956561_241116'},
  '00439': {'GT': 0, 'Acc': ' 90.00%', 'Pred': [27, 3], 'edfname': '00760780_141118'},
  '00369': {'GT': 1, 'Acc': ' 20.00%', 'Pred': [24, 6], 'edfname': '00715828_111016'},
  '00955': {'GT': 1, 'Acc': ' 66.67%', 'Pred': [10, 20], 'edfname': '01178888_161117'},
  '00300': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00671379_290617'},
  '01196': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '01307883_100217'},
  '00923': {'GT': 0, 'Acc': ' 33.33%', 'Pred': [10, 20], 'edfname': '01155730_070514'},
  '00058': {'GT': 0, 'Acc': ' 60.00%', 'Pred': [18, 12], 'edfname': '00285244_020414'},
  '00584': {'GT': 1, 'Acc': ' 43.33%', 'Pred': [17, 13], 'edfname': '00891889_060717'},
  '00749': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '01027623_260916'},
  '01334': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01396872_021018'},
  '00588': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00895530_090616'},
  '00679': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00963069_150618'},
  '00385': {'GT': 0, 'Acc': '  0.00%', 'Pred': [0, 30], 'edfname': '00723232_270318'},
  '00018': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00128526_180817'},
  '01281': {'GT': 1, 'Acc': ' 50.00%', 'Pred': [15, 15], 'edfname': '01358607_280918'},
  '00651': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00951808_251116'},
  '01253': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01344212_240817'},
  '01035': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01231654_260417'},
  '00551': {'GT': 1, 'Acc': ' 86.67%', 'Pred': [4, 26], 'edfname': '00865039_170816'},
  '00870': {'GT': 0, 'Acc': ' 86.67%', 'Pred': [26, 4], 'edfname': '01139947_120214'},
  '00578': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00888613_080618'},
  '00730': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01011922_270815'},
  '00516': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00823206_130514'},
  '01330': {'GT': 0, 'Acc': ' 83.33%', 'Pred': [25, 5], 'edfname': '01392885_240718'},
  '00944': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01168853_070316'},
  '00125': {'GT': 0, 'Acc': ' 86.67%', 'Pred': [26, 4], 'edfname': '00418981_090316'},
  '00508': {'GT': 0, 'Acc': ' 86.67%', 'Pred': [26, 4], 'edfname': '00817022_010415'},
  '01317': {'GT': 1, 'Acc': ' 63.33%', 'Pred': [11, 19], 'edfname': '01381606_160518'},
  '00608': {'GT': 1, 'Acc': '  0.00%', 'Pred': [30, 0], 'edfname': '00907971_030217'},
  '00471': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00784417_100315'},
  '00821': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01128393_300715'},
  '00122': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00416942_190516'},
  '01007': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01211467_070415'},
  '01247': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01339759_310717'},
  '00173': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00601028_290618'},
  '01026': {'GT': 0, 'Acc': ' 86.67%', 'Pred': [26, 4], 'edfname': '01225123_050815'},
  '01018': {'GT': 1, 'Acc': '  0.00%', 'Pred': [30, 0], 'edfname': '01216443_240518'},
  '00418': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '00745209_220916'},
  '01206': {'GT': 1, 'Acc': '  6.67%', 'Pred': [28, 2], 'edfname': '01314786_200317'},
  '01215': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01321744_130417'},
  '01105': {'GT': 0, 'Acc': ' 30.00%', 'Pred': [9, 21], 'edfname': '01266696_110516'},
  '00598': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '00899964_110414'},
  '00851': {'GT': 0, 'Acc': ' 73.33%', 'Pred': [22, 8], 'edfname': '01138297_230114'},
  '01138': {'GT': 0, 'Acc': ' 60.00%', 'Pred': [18, 12], 'edfname': '01281605_070716'},
  '00079': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00325929_170119'},
  '00245': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00637371_050917'},
  '00591': {'GT': 0, 'Acc': ' 73.33%', 'Pred': [22, 8], 'edfname': '00896386_240914'},
  '00329': {'GT': 0, 'Acc': ' 76.67%', 'Pred': [23, 7], 'edfname': '00685248_150414'},
  '00272': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00651389_281016'},
  '00176': {'GT': 0, 'Acc': ' 50.00%', 'Pred': [15, 15], 'edfname': '00602435_270217'},
  '00807': {'GT': 1, 'Acc': ' 13.33%', 'Pred': [26, 4], 'edfname': '01112291_231115'},
  '00271': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00651252_140618'},
  '00712': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00988278_210915'},
  '00974': {'GT': 1, 'Acc': ' 43.33%', 'Pred': [17, 13], 'edfname': '01193508_171214'},
  '01163': {'GT': 1, 'Acc': '  0.00%', 'Pred': [30, 0], 'edfname': '01296342_141116'}}

1D CNN: ResNet-like model

class BasicResBlock(nn.Module):
    expansion: int = 1

    def __init__(self, c_in, c_out, kernel_size, stride) -> None:
        super().__init__()
        self.conv1 = nn.Conv1d(in_channels=c_in, out_channels=c_out, 
                               kernel_size=kernel_size, stride=stride, 
                               padding=kernel_size//2, bias=False)
        self.bn1 = nn.BatchNorm1d(c_out)

        self.conv2 = nn.Conv1d(in_channels=c_out, out_channels=c_out, 
                               kernel_size=kernel_size, stride=1, 
                               padding=kernel_size//2, bias=False)
        self.bn2 = nn.BatchNorm1d(c_out)

        self.relu = nn.ReLU(inplace=True)
        
        self.downsample = None
        if stride != 1 or c_in != c_out:
            self.downsample = nn.Sequential(
                nn.Conv1d(in_channels=c_in, out_channels=c_out, 
                          kernel_size=1, stride=stride, bias=False),
                nn.BatchNorm1d(c_out)
            )
                    
    def forward(self, x: torch.Tensor) -> torch.Tensor:
        identity = x
        
        x = self.conv1(x)
        x = self.bn1(x)
        x = self.relu(x)
        
        x = self.conv2(x)
        x = self.bn2(x)
        if self.downsample is not None:
            identity = self.downsample(identity)
        x = self.relu(x + identity)
        
        return x

class BottleneckBlock(nn.Module):
    expansion: int = 4
        
    def __init__(self, c_in, c_out, kernel_size, stride) -> None:
        super().__init__()
        width = c_out
        self.conv1 = nn.Conv1d(in_channels=c_in, out_channels=width, 
                               kernel_size=1, stride=1, bias=False)
        self.bn1 = nn.BatchNorm1d(width)

        self.conv2 = nn.Conv1d(in_channels=width, out_channels=width, 
                               kernel_size=kernel_size, stride=stride, 
                               padding=kernel_size//2, bias=False)
        self.bn2 = nn.BatchNorm1d(width)

        self.conv3 = nn.Conv1d(in_channels=width, out_channels=c_out*self.expansion, 
                               kernel_size=1, stride=1, bias=False)
        self.bn3 = nn.BatchNorm1d(c_out*self.expansion)
        
        self.relu = nn.ReLU(inplace=True)
        
        self.downsample = None
        if stride != 1 or c_in != c_out*self.expansion:
            self.downsample = nn.Sequential(
                nn.Conv1d(in_channels=c_in, out_channels=c_out*self.expansion, 
                          kernel_size=1, stride=stride, bias=False),
                nn.BatchNorm1d(c_out*self.expansion)
            )
                    
    def forward(self, x: torch.Tensor) -> torch.Tensor:
        identity = x
        
        x = self.conv1(x)
        x = self.bn1(x)
        x = self.relu(x)
        
        x = self.conv2(x)
        x = self.bn2(x)
        x = self.relu(x)
        
        x = self.conv3(x)
        x = self.bn3(x)
        if self.downsample is not None:
            identity = self.downsample(identity)
            
        x = self.relu(x + identity)
        
        return x

class ResNet(nn.Module):
    def __init__(self, 
                 block: Type[Union[BasicResBlock, BottleneckBlock]], 
                 conv_layers: List[int],
                 n_fc: int,
                 n_input=20,
                 n_output=3,
                 n_start=64,
                 kernel_size=9, 
                 use_age=True, 
                 final_pool='average') -> None:
        
        super().__init__()
        
        if final_pool not in {'average', 'max'}:
            raise ValueError("final_pool must be set to one of ['average', 'max']")        

        self.c_current = n_start
        self.use_age = use_age
        
        self.input_stage = nn.Sequential(
            nn.Conv1d(in_channels=n_input, out_channels=n_start, 
                      kernel_size=kernel_size*3, stride=2,
                      padding=(kernel_size*3)//2, bias=False),
            nn.BatchNorm1d(n_start), 
            nn.ReLU(),
        )
        
        self.conv_stage1 = self._make_conv_layer(block, conv_layers[0], n_start, kernel_size, stride=3)
        self.conv_stage2 = self._make_conv_layer(block, conv_layers[1], n_start*2, kernel_size, stride=3)
        self.conv_stage3 = self._make_conv_layer(block, conv_layers[2], n_start*4, kernel_size, stride=3)
        self.conv_stage4 = self._make_conv_layer(block, conv_layers[3], n_start*8, kernel_size, stride=3)
        
        if final_pool == 'average':
            self.final_pool = nn.AdaptiveAvgPool1d(1)
        elif final_pool == 'max':
            self.final_pool = nn.AdaptiveMaxPool1d(1)
        
        fc_layers = []        
        if self.use_age:
            self.c_current = self.c_current + 1
        
        for l in range(n_fc):
            layer = nn.Sequential(nn.Linear(self.c_current, self.c_current // 2, bias=False),
                                  nn.Dropout(p=0.1),
                                  nn.BatchNorm1d(self.c_current // 2), 
                                  nn.ReLU())
            self.c_current = self.c_current // 2
            fc_layers.append(layer)
        fc_layers.append(nn.Linear(self.c_current, n_output))
        self.fc_stage = nn.Sequential(*fc_layers)
        
    def reset_weights(self):
        for m in self.modules():
            if hasattr(m, 'reset_parameters'):
                m.reset_parameters()
        
    def _make_conv_layer(self, block: Type[Union[BasicResBlock, BottleneckBlock]], 
                         n_block: int, c_out: int, kernel_size: int, stride: int = 1) -> nn.Sequential:
        layers = []
        c_in = self.c_current
        layers.append(block(c_in, c_out, kernel_size, stride=1))

        c_in = c_out * block.expansion
        self.c_current = c_in
        for _ in range(1, n_block):
            layers.append(block(c_in, c_out, kernel_size, stride=1))
            
        layers.append(nn.MaxPool1d(kernel_size=stride))
            
        return nn.Sequential(*layers)

    def forward(self, x, age, print_shape=False):
        x = self.input_stage(x)
        
        x = self.conv_stage1(x)
        x = self.conv_stage2(x)
        x = self.conv_stage3(x)
        x = self.conv_stage4(x)

        if print_shape:
            print('Shape right before squeezing:', x.shape)
                
        x = self.final_pool(x).squeeze()
        if self.use_age:
            x = torch.cat((x, age.reshape(-1, 1)), dim=1)
        x = self.fc_stage(x)
        
        return x
        # return F.log_softmax(x, dim=2)

model = ResNet(block=BottleneckBlock, 
               conv_layers=[2, 2, 2, 2], 
               n_fc=3, 
               n_input=train_dataset[0]['signal'].shape[0], 
               n_output=2, 
               n_start=64,
               kernel_size=9, 
               use_age=True, 
               final_pool='max')
model = model.to(device, dtype=torch.float32)
print(model)
print()

# tensorboard visualization
visualize_network_tensorboard(model, 'ResNet-like')

# number of parameters
n = count_parameters(model)
print(f'The Number of parameters of the model: {n:,}')

ResNet(
  (input_stage): Sequential(
    (0): Conv1d(20, 64, kernel_size=(27,), stride=(2,), padding=(13,), bias=False)
    (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (2): ReLU()
  )
  (conv_stage1): Sequential(
    (0): BottleneckBlock(
      (conv1): Conv1d(64, 64, kernel_size=(1,), stride=(1,), bias=False)
      (bn1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (conv2): Conv1d(64, 64, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
      (bn2): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (conv3): Conv1d(64, 256, kernel_size=(1,), stride=(1,), bias=False)
      (bn3): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (relu): ReLU(inplace=True)
      (downsample): Sequential(
        (0): Conv1d(64, 256, kernel_size=(1,), stride=(1,), bias=False)
        (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
    )
    (1): BottleneckBlock(
      (conv1): Conv1d(256, 64, kernel_size=(1,), stride=(1,), bias=False)
      (bn1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (conv2): Conv1d(64, 64, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
      (bn2): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (conv3): Conv1d(64, 256, kernel_size=(1,), stride=(1,), bias=False)
      (bn3): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (relu): ReLU(inplace=True)
    )
    (2): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)
  )
  (conv_stage2): Sequential(
    (0): BottleneckBlock(
      (conv1): Conv1d(256, 128, kernel_size=(1,), stride=(1,), bias=False)
      (bn1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (conv2): Conv1d(128, 128, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
      (bn2): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (conv3): Conv1d(128, 512, kernel_size=(1,), stride=(1,), bias=False)
      (bn3): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (relu): ReLU(inplace=True)
      (downsample): Sequential(
        (0): Conv1d(256, 512, kernel_size=(1,), stride=(1,), bias=False)
        (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
    )
    (1): BottleneckBlock(
      (conv1): Conv1d(512, 128, kernel_size=(1,), stride=(1,), bias=False)
      (bn1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (conv2): Conv1d(128, 128, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
      (bn2): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (conv3): Conv1d(128, 512, kernel_size=(1,), stride=(1,), bias=False)
      (bn3): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (relu): ReLU(inplace=True)
    )
    (2): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)
  )
  (conv_stage3): Sequential(
    (0): BottleneckBlock(
      (conv1): Conv1d(512, 256, kernel_size=(1,), stride=(1,), bias=False)
      (bn1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (conv2): Conv1d(256, 256, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
      (bn2): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (conv3): Conv1d(256, 1024, kernel_size=(1,), stride=(1,), bias=False)
      (bn3): BatchNorm1d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (relu): ReLU(inplace=True)
      (downsample): Sequential(
        (0): Conv1d(512, 1024, kernel_size=(1,), stride=(1,), bias=False)
        (1): BatchNorm1d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
    )
    (1): BottleneckBlock(
      (conv1): Conv1d(1024, 256, kernel_size=(1,), stride=(1,), bias=False)
      (bn1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (conv2): Conv1d(256, 256, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
      (bn2): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (conv3): Conv1d(256, 1024, kernel_size=(1,), stride=(1,), bias=False)
      (bn3): BatchNorm1d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (relu): ReLU(inplace=True)
    )
    (2): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)
  )
  (conv_stage4): Sequential(
    (0): BottleneckBlock(
      (conv1): Conv1d(1024, 512, kernel_size=(1,), stride=(1,), bias=False)
      (bn1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (conv2): Conv1d(512, 512, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
      (bn2): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (conv3): Conv1d(512, 2048, kernel_size=(1,), stride=(1,), bias=False)
      (bn3): BatchNorm1d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (relu): ReLU(inplace=True)
      (downsample): Sequential(
        (0): Conv1d(1024, 2048, kernel_size=(1,), stride=(1,), bias=False)
        (1): BatchNorm1d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
    )
    (1): BottleneckBlock(
      (conv1): Conv1d(2048, 512, kernel_size=(1,), stride=(1,), bias=False)
      (bn1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (conv2): Conv1d(512, 512, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
      (bn2): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (conv3): Conv1d(512, 2048, kernel_size=(1,), stride=(1,), bias=False)
      (bn3): BatchNorm1d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (relu): ReLU(inplace=True)
    )
    (2): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)
  )
  (final_pool): AdaptiveMaxPool1d(output_size=1)
  (fc_stage): Sequential(
    (0): Sequential(
      (0): Linear(in_features=2049, out_features=1024, bias=False)
      (1): Dropout(p=0.1, inplace=False)
      (2): BatchNorm1d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (3): ReLU()
    )
    (1): Sequential(
      (0): Linear(in_features=1024, out_features=512, bias=False)
      (1): Dropout(p=0.1, inplace=False)
      (2): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (3): ReLU()
    )
    (2): Sequential(
      (0): Linear(in_features=512, out_features=256, bias=False)
      (1): Dropout(p=0.1, inplace=False)
      (2): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (3): ReLU()
    )
    (3): Linear(in_features=256, out_features=2, bias=True)
  )
)

Shape right before squeezing: torch.Size([32, 2048, 12])
The Number of parameters of the model: 16,728,962

record = learning_rate_search(model, 
                              min_log_lr=-4.5, 
                              max_log_lr=-1.4, 
                              trials=300, 
                              epochs=1)
draw_learning_rate_record(record)
best_log_lr = record[np.argmax(np.array([v for lr, v in record]))][0]

# best_log_lr = -3.5
print('best_log_lr:', best_log_lr)

best_log_lr: -2.561406555942617

# reduce the learning after [lr_schedule_step] epochs by a factor of 10
n_epoch = 500
lr_schedule_step = 200
log_interval = len(train_loader) // 2

loss_history = []
train_acc_history = []
val_acc_history = []
best_val_acc = 0

model.reset_weights()
optimizer = optim.AdamW(model.parameters(), lr=10 ** best_log_lr, weight_decay=0.0001)
scheduler = optim.lr_scheduler.StepLR(optimizer, step_size=lr_schedule_step, gamma=0.1)

print(f'{"*"*40} Training Starts {"*"*40}')

for epoch in tqdm(range(1, n_epoch + 1)):
    print(f'{"-"*30} Epoch {epoch:03d} / {n_epoch:03d}, Learning rate: {optimizer.param_groups[-1]["lr"]:.2e} {"-"*30}')
    
    # train
    loss, train_accuracy, train_confusion = train_one_epoch(model, optimizer, log_interval)
    loss_history.extend(loss)
    train_acc_history.append(train_accuracy)
    
    # validation
    val_accuracy, val_confusion = check_val_accuracy(model, repeat=5)
    val_acc_history.append(val_accuracy)
    
    if best_val_acc < val_accuracy:
        best_val_acc = val_accuracy
        best_model_state = deepcopy(model.state_dict())
    
    # learning rate schedule
    scheduler.step()
    
    print()
    print(f'* Train accuracy / confusion: {train_accuracy:.2f}% / {train_confusion.tolist()}, ')
    print(f'* Val   accuracy / confusion: {val_accuracy:.2f}% / {val_confusion.tolist()}')
    print()

print(f'{"*"*40} Training Ends {"*"*40}')

# draw the training loss plot
draw_loss_plot(loss_history)
draw_accuracy_history(train_acc_history, val_acc_history)
    
# test the last model
last_model_state = deepcopy(model.state_dict())
last_test_accuracy, last_test_confusion, last_test_debug = check_test_accuracy(model, repeat=30)

print(f'- Test accuracy (last model): {last_test_accuracy:.2f}%')
print('- Confusion matrix (last model):\n', last_test_confusion)
print()

draw_confusion(last_test_confusion)

# test the best model
model.load_state_dict(best_model_state)
best_test_accuracy, best_test_confusion, best_test_debug = check_test_accuracy(model, repeat=30)

print(f'- Test accuracy (best model): {best_test_accuracy:.2f}%')
print('- Confusion matrix (best model):\n', best_test_confusion)
print()

draw_confusion(best_test_confusion)

**************************************** Training Starts ****************************************

------------------------------ Epoch 001 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.644670
- Iter 028 / 029, Loss: 0.745010

* Train accuracy / confusion: 59.27% / [[57, 305], [73, 493]], 
* Val   accuracy / confusion: 57.80% / [[82, 148], [101, 259]]

------------------------------ Epoch 002 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.638908
- Iter 028 / 029, Loss: 0.649859

* Train accuracy / confusion: 60.24% / [[9, 354], [15, 550]], 
* Val   accuracy / confusion: 60.17% / [[15, 215], [20, 340]]

------------------------------ Epoch 003 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.672112
- Iter 028 / 029, Loss: 0.867415

* Train accuracy / confusion: 60.24% / [[14, 349], [20, 545]], 
* Val   accuracy / confusion: 57.12% / [[18, 212], [41, 319]]

------------------------------ Epoch 004 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.774632
- Iter 028 / 029, Loss: 0.723529

* Train accuracy / confusion: 59.05% / [[41, 324], [56, 507]], 
* Val   accuracy / confusion: 46.27% / [[177, 53], [264, 96]]

------------------------------ Epoch 005 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.680691
- Iter 028 / 029, Loss: 0.692041

* Train accuracy / confusion: 60.13% / [[12, 350], [20, 546]], 
* Val   accuracy / confusion: 58.14% / [[54, 176], [71, 289]]

------------------------------ Epoch 006 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.616167
- Iter 028 / 029, Loss: 0.679129

* Train accuracy / confusion: 58.51% / [[28, 334], [51, 515]], 
* Val   accuracy / confusion: 61.02% / [[0, 230], [0, 360]]

------------------------------ Epoch 007 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.636549
- Iter 028 / 029, Loss: 0.612225

* Train accuracy / confusion: 60.88% / [[45, 316], [47, 520]], 
* Val   accuracy / confusion: 58.64% / [[31, 199], [45, 315]]

------------------------------ Epoch 008 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.667415
- Iter 028 / 029, Loss: 0.634167

* Train accuracy / confusion: 59.05% / [[15, 349], [31, 533]], 
* Val   accuracy / confusion: 58.81% / [[44, 186], [57, 303]]

------------------------------ Epoch 009 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.648577
- Iter 028 / 029, Loss: 0.637284

* Train accuracy / confusion: 59.59% / [[15, 349], [26, 538]], 
* Val   accuracy / confusion: 61.02% / [[0, 230], [0, 360]]

------------------------------ Epoch 010 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.682927
- Iter 028 / 029, Loss: 0.707139

* Train accuracy / confusion: 59.81% / [[10, 355], [18, 545]], 
* Val   accuracy / confusion: 59.49% / [[14, 216], [23, 337]]

------------------------------ Epoch 011 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.658257
- Iter 028 / 029, Loss: 0.760335

* Train accuracy / confusion: 60.24% / [[10, 352], [17, 549]], 
* Val   accuracy / confusion: 61.02% / [[0, 230], [0, 360]]

------------------------------ Epoch 012 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.675185
- Iter 028 / 029, Loss: 0.677406

* Train accuracy / confusion: 60.56% / [[4, 355], [11, 558]], 
* Val   accuracy / confusion: 61.02% / [[0, 230], [0, 360]]

------------------------------ Epoch 013 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.663284
- Iter 028 / 029, Loss: 0.727438

* Train accuracy / confusion: 60.67% / [[10, 350], [15, 553]], 
* Val   accuracy / confusion: 61.02% / [[0, 230], [0, 360]]

------------------------------ Epoch 014 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.703057
- Iter 028 / 029, Loss: 0.655900

* Train accuracy / confusion: 60.99% / [[23, 339], [23, 543]], 
* Val   accuracy / confusion: 61.02% / [[0, 230], [0, 360]]

------------------------------ Epoch 015 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.680526
- Iter 028 / 029, Loss: 0.702060

* Train accuracy / confusion: 60.45% / [[32, 335], [32, 529]], 
* Val   accuracy / confusion: 59.49% / [[20, 210], [29, 331]]

------------------------------ Epoch 016 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.732440
- Iter 028 / 029, Loss: 0.695343

* Train accuracy / confusion: 60.24% / [[19, 343], [26, 540]], 
* Val   accuracy / confusion: 61.02% / [[6, 224], [6, 354]]

------------------------------ Epoch 017 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.771961
- Iter 028 / 029, Loss: 0.789541

* Train accuracy / confusion: 59.59% / [[12, 352], [23, 541]], 
* Val   accuracy / confusion: 61.02% / [[0, 230], [0, 360]]

------------------------------ Epoch 018 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.652855
- Iter 028 / 029, Loss: 0.718768

* Train accuracy / confusion: 60.02% / [[25, 334], [37, 532]], 
* Val   accuracy / confusion: 55.76% / [[25, 205], [56, 304]]

------------------------------ Epoch 019 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.657364
- Iter 028 / 029, Loss: 0.717036

* Train accuracy / confusion: 61.64% / [[13, 348], [8, 559]], 
* Val   accuracy / confusion: 61.02% / [[0, 230], [0, 360]]

------------------------------ Epoch 020 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.637488
- Iter 028 / 029, Loss: 0.624419

* Train accuracy / confusion: 60.56% / [[12, 350], [16, 550]], 
* Val   accuracy / confusion: 61.02% / [[0, 230], [0, 360]]

------------------------------ Epoch 021 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.626449
- Iter 028 / 029, Loss: 0.629064

* Train accuracy / confusion: 61.21% / [[5, 354], [6, 563]], 
* Val   accuracy / confusion: 58.47% / [[9, 221], [24, 336]]

------------------------------ Epoch 022 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.700085
- Iter 028 / 029, Loss: 0.674854

* Train accuracy / confusion: 60.02% / [[11, 352], [19, 546]], 
* Val   accuracy / confusion: 59.66% / [[22, 208], [30, 330]]

------------------------------ Epoch 023 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.690385
- Iter 028 / 029, Loss: 0.634087

* Train accuracy / confusion: 60.02% / [[39, 325], [46, 518]], 
* Val   accuracy / confusion: 60.00% / [[21, 209], [27, 333]]

------------------------------ Epoch 024 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.664304
- Iter 028 / 029, Loss: 0.678125

* Train accuracy / confusion: 60.24% / [[9, 353], [16, 550]], 
* Val   accuracy / confusion: 61.02% / [[0, 230], [0, 360]]

------------------------------ Epoch 025 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.694866
- Iter 028 / 029, Loss: 0.644154

* Train accuracy / confusion: 60.56% / [[6, 355], [11, 556]], 
* Val   accuracy / confusion: 57.97% / [[13, 217], [31, 329]]

------------------------------ Epoch 026 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.814333
- Iter 028 / 029, Loss: 0.616311

* Train accuracy / confusion: 60.99% / [[13, 346], [16, 553]], 
* Val   accuracy / confusion: 61.02% / [[0, 230], [0, 360]]

------------------------------ Epoch 027 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.723666
- Iter 028 / 029, Loss: 0.629668

* Train accuracy / confusion: 60.02% / [[19, 347], [24, 538]], 
* Val   accuracy / confusion: 61.53% / [[4, 226], [1, 359]]

------------------------------ Epoch 028 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.650317
- Iter 028 / 029, Loss: 0.702771

* Train accuracy / confusion: 60.13% / [[3, 356], [14, 555]], 
* Val   accuracy / confusion: 61.19% / [[1, 229], [0, 360]]

------------------------------ Epoch 029 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.609975
- Iter 028 / 029, Loss: 0.682831

* Train accuracy / confusion: 60.45% / [[10, 352], [15, 551]], 
* Val   accuracy / confusion: 61.02% / [[0, 230], [0, 360]]

------------------------------ Epoch 030 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.673318
- Iter 028 / 029, Loss: 0.698171

* Train accuracy / confusion: 60.34% / [[10, 353], [15, 550]], 
* Val   accuracy / confusion: 60.51% / [[20, 210], [23, 337]]

------------------------------ Epoch 031 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.718451
- Iter 028 / 029, Loss: 0.721166

* Train accuracy / confusion: 59.38% / [[32, 332], [45, 519]], 
* Val   accuracy / confusion: 56.61% / [[9, 221], [35, 325]]

------------------------------ Epoch 032 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.785854
- Iter 028 / 029, Loss: 0.669974

* Train accuracy / confusion: 60.88% / [[1, 359], [4, 564]], 
* Val   accuracy / confusion: 61.02% / [[0, 230], [0, 360]]

------------------------------ Epoch 033 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.598002
- Iter 028 / 029, Loss: 0.697453

* Train accuracy / confusion: 60.34% / [[14, 349], [19, 546]], 
* Val   accuracy / confusion: 58.31% / [[34, 196], [50, 310]]

------------------------------ Epoch 034 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.647858
- Iter 028 / 029, Loss: 0.811316

* Train accuracy / confusion: 59.70% / [[17, 345], [29, 537]], 
* Val   accuracy / confusion: 61.53% / [[63, 167], [60, 300]]

------------------------------ Epoch 035 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.733414
- Iter 028 / 029, Loss: 0.652821

* Train accuracy / confusion: 60.02% / [[11, 353], [18, 546]], 
* Val   accuracy / confusion: 61.02% / [[0, 230], [0, 360]]

------------------------------ Epoch 036 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.678377
- Iter 028 / 029, Loss: 0.704869

* Train accuracy / confusion: 60.45% / [[16, 348], [19, 545]], 
* Val   accuracy / confusion: 61.02% / [[0, 230], [0, 360]]

------------------------------ Epoch 037 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.630756
- Iter 028 / 029, Loss: 0.728877

* Train accuracy / confusion: 61.10% / [[9, 357], [4, 558]], 
* Val   accuracy / confusion: 59.49% / [[50, 180], [59, 301]]

------------------------------ Epoch 038 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.797622
- Iter 028 / 029, Loss: 0.717088

* Train accuracy / confusion: 61.31% / [[48, 311], [48, 521]], 
* Val   accuracy / confusion: 61.36% / [[3, 227], [1, 359]]

------------------------------ Epoch 039 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.676870
- Iter 028 / 029, Loss: 0.718525

* Train accuracy / confusion: 61.53% / [[12, 351], [6, 559]], 
* Val   accuracy / confusion: 61.02% / [[0, 230], [0, 360]]

------------------------------ Epoch 040 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.658629
- Iter 028 / 029, Loss: 0.706446

* Train accuracy / confusion: 65.41% / [[105, 257], [64, 502]], 
* Val   accuracy / confusion: 61.02% / [[3, 227], [3, 357]]

------------------------------ Epoch 041 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.516066
- Iter 028 / 029, Loss: 0.611194

* Train accuracy / confusion: 67.56% / [[178, 184], [117, 449]], 
* Val   accuracy / confusion: 67.97% / [[47, 183], [6, 354]]

------------------------------ Epoch 042 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.503231
- Iter 028 / 029, Loss: 0.570772

* Train accuracy / confusion: 68.00% / [[143, 219], [78, 488]], 
* Val   accuracy / confusion: 64.07% / [[19, 211], [1, 359]]

------------------------------ Epoch 043 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.592222
- Iter 028 / 029, Loss: 0.555303

* Train accuracy / confusion: 71.88% / [[207, 150], [111, 460]], 
* Val   accuracy / confusion: 60.51% / [[10, 220], [13, 347]]

------------------------------ Epoch 044 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.524938
- Iter 028 / 029, Loss: 0.704303

* Train accuracy / confusion: 70.15% / [[165, 193], [84, 486]], 
* Val   accuracy / confusion: 71.69% / [[91, 139], [28, 332]]

------------------------------ Epoch 045 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.421414
- Iter 028 / 029, Loss: 0.698905

* Train accuracy / confusion: 69.94% / [[160, 202], [77, 489]], 
* Val   accuracy / confusion: 39.83% / [[211, 19], [336, 24]]

------------------------------ Epoch 046 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.607128
- Iter 028 / 029, Loss: 0.613303

* Train accuracy / confusion: 67.89% / [[174, 187], [111, 456]], 
* Val   accuracy / confusion: 59.83% / [[186, 44], [193, 167]]

------------------------------ Epoch 047 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.587314
- Iter 028 / 029, Loss: 0.563967

* Train accuracy / confusion: 63.90% / [[117, 247], [88, 476]], 
* Val   accuracy / confusion: 59.66% / [[197, 33], [205, 155]]

------------------------------ Epoch 048 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.554210
- Iter 028 / 029, Loss: 0.589354

* Train accuracy / confusion: 68.00% / [[164, 197], [100, 467]], 
* Val   accuracy / confusion: 65.59% / [[160, 70], [133, 227]]

------------------------------ Epoch 049 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.492169
- Iter 028 / 029, Loss: 0.581100

* Train accuracy / confusion: 69.72% / [[183, 177], [104, 464]], 
* Val   accuracy / confusion: 68.64% / [[108, 122], [63, 297]]

------------------------------ Epoch 050 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.684753
- Iter 028 / 029, Loss: 0.790375

* Train accuracy / confusion: 69.83% / [[178, 185], [95, 470]], 
* Val   accuracy / confusion: 66.10% / [[32, 198], [2, 358]]

------------------------------ Epoch 051 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.659775
- Iter 028 / 029, Loss: 0.532649

* Train accuracy / confusion: 69.40% / [[185, 180], [104, 459]], 
* Val   accuracy / confusion: 75.59% / [[141, 89], [55, 305]]

------------------------------ Epoch 052 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.512051
- Iter 028 / 029, Loss: 0.638380

* Train accuracy / confusion: 71.66% / [[182, 179], [84, 483]], 
* Val   accuracy / confusion: 75.42% / [[118, 112], [33, 327]]

------------------------------ Epoch 053 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.477207
- Iter 028 / 029, Loss: 0.549748

* Train accuracy / confusion: 70.15% / [[188, 176], [101, 463]], 
* Val   accuracy / confusion: 71.02% / [[67, 163], [8, 352]]

------------------------------ Epoch 054 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.799358
- Iter 028 / 029, Loss: 0.388486

* Train accuracy / confusion: 70.69% / [[197, 163], [109, 459]], 
* Val   accuracy / confusion: 75.08% / [[114, 116], [31, 329]]

------------------------------ Epoch 055 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.431293
- Iter 028 / 029, Loss: 0.717996

* Train accuracy / confusion: 69.83% / [[197, 167], [113, 451]], 
* Val   accuracy / confusion: 70.68% / [[129, 101], [72, 288]]

------------------------------ Epoch 056 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.439072
- Iter 028 / 029, Loss: 0.597329

* Train accuracy / confusion: 71.77% / [[198, 167], [95, 468]], 
* Val   accuracy / confusion: 74.92% / [[129, 101], [47, 313]]

------------------------------ Epoch 057 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.564264
- Iter 028 / 029, Loss: 0.597876

* Train accuracy / confusion: 70.80% / [[208, 155], [116, 449]], 
* Val   accuracy / confusion: 72.88% / [[132, 98], [62, 298]]

------------------------------ Epoch 058 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.542687
- Iter 028 / 029, Loss: 0.418623

* Train accuracy / confusion: 72.52% / [[193, 167], [88, 480]], 
* Val   accuracy / confusion: 74.24% / [[103, 127], [25, 335]]

------------------------------ Epoch 059 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.563500
- Iter 028 / 029, Loss: 0.512664

* Train accuracy / confusion: 69.18% / [[183, 181], [105, 459]], 
* Val   accuracy / confusion: 73.90% / [[138, 92], [62, 298]]

------------------------------ Epoch 060 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.437535
- Iter 028 / 029, Loss: 0.475196

* Train accuracy / confusion: 74.03% / [[214, 149], [92, 473]], 
* Val   accuracy / confusion: 74.07% / [[130, 100], [53, 307]]

------------------------------ Epoch 061 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.528091
- Iter 028 / 029, Loss: 0.534164

* Train accuracy / confusion: 73.06% / [[216, 146], [104, 462]], 
* Val   accuracy / confusion: 75.25% / [[146, 84], [62, 298]]

------------------------------ Epoch 062 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.444561
- Iter 028 / 029, Loss: 0.572196

* Train accuracy / confusion: 72.84% / [[217, 146], [106, 459]], 
* Val   accuracy / confusion: 70.68% / [[171, 59], [114, 246]]

------------------------------ Epoch 063 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.496806
- Iter 028 / 029, Loss: 0.748794

* Train accuracy / confusion: 73.06% / [[227, 135], [115, 451]], 
* Val   accuracy / confusion: 74.75% / [[108, 122], [27, 333]]

------------------------------ Epoch 064 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.574221
- Iter 028 / 029, Loss: 0.550376

* Train accuracy / confusion: 73.92% / [[223, 137], [105, 463]], 
* Val   accuracy / confusion: 75.76% / [[128, 102], [41, 319]]

------------------------------ Epoch 065 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.524427
- Iter 028 / 029, Loss: 0.512906

* Train accuracy / confusion: 72.31% / [[206, 153], [104, 465]], 
* Val   accuracy / confusion: 74.24% / [[112, 118], [34, 326]]

------------------------------ Epoch 066 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.635360
- Iter 028 / 029, Loss: 0.497736

* Train accuracy / confusion: 72.41% / [[189, 171], [85, 483]], 
* Val   accuracy / confusion: 72.54% / [[147, 83], [79, 281]]

------------------------------ Epoch 067 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.534143
- Iter 028 / 029, Loss: 0.451379

* Train accuracy / confusion: 73.38% / [[219, 144], [103, 462]], 
* Val   accuracy / confusion: 77.63% / [[130, 100], [32, 328]]

------------------------------ Epoch 068 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.395060
- Iter 028 / 029, Loss: 0.797427

* Train accuracy / confusion: 73.60% / [[216, 146], [99, 467]], 
* Val   accuracy / confusion: 75.08% / [[125, 105], [42, 318]]

------------------------------ Epoch 069 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.517716
- Iter 028 / 029, Loss: 0.623880

* Train accuracy / confusion: 72.95% / [[209, 153], [98, 468]], 
* Val   accuracy / confusion: 74.07% / [[101, 129], [24, 336]]

------------------------------ Epoch 070 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.450777
- Iter 028 / 029, Loss: 0.591589

* Train accuracy / confusion: 73.60% / [[214, 151], [94, 469]], 
* Val   accuracy / confusion: 74.58% / [[125, 105], [45, 315]]

------------------------------ Epoch 071 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.488220
- Iter 028 / 029, Loss: 0.587824

* Train accuracy / confusion: 74.14% / [[217, 145], [95, 471]], 
* Val   accuracy / confusion: 72.71% / [[129, 101], [60, 300]]

------------------------------ Epoch 072 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.560366
- Iter 028 / 029, Loss: 0.404665

* Train accuracy / confusion: 75.00% / [[217, 145], [87, 479]], 
* Val   accuracy / confusion: 72.54% / [[102, 128], [34, 326]]

------------------------------ Epoch 073 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.662213
- Iter 028 / 029, Loss: 0.674119

* Train accuracy / confusion: 72.95% / [[203, 158], [93, 474]], 
* Val   accuracy / confusion: 76.44% / [[116, 114], [25, 335]]

------------------------------ Epoch 074 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.571250
- Iter 028 / 029, Loss: 0.641377

* Train accuracy / confusion: 72.20% / [[199, 164], [94, 471]], 
* Val   accuracy / confusion: 75.76% / [[112, 118], [25, 335]]

------------------------------ Epoch 075 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.395425
- Iter 028 / 029, Loss: 0.478034

* Train accuracy / confusion: 73.06% / [[211, 153], [97, 467]], 
* Val   accuracy / confusion: 75.93% / [[137, 93], [49, 311]]

------------------------------ Epoch 076 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.660930
- Iter 028 / 029, Loss: 0.677270

* Train accuracy / confusion: 72.84% / [[205, 158], [94, 471]], 
* Val   accuracy / confusion: 76.27% / [[136, 94], [46, 314]]

------------------------------ Epoch 077 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.646968
- Iter 028 / 029, Loss: 0.631745

* Train accuracy / confusion: 71.55% / [[188, 170], [94, 476]], 
* Val   accuracy / confusion: 69.66% / [[79, 151], [28, 332]]

------------------------------ Epoch 078 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.447319
- Iter 028 / 029, Loss: 0.650552

* Train accuracy / confusion: 72.20% / [[210, 151], [107, 460]], 
* Val   accuracy / confusion: 74.92% / [[142, 88], [60, 300]]

------------------------------ Epoch 079 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.705333
- Iter 028 / 029, Loss: 0.531653

* Train accuracy / confusion: 73.92% / [[210, 151], [91, 476]], 
* Val   accuracy / confusion: 76.10% / [[113, 117], [24, 336]]

------------------------------ Epoch 080 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.497228
- Iter 028 / 029, Loss: 0.389785

* Train accuracy / confusion: 73.60% / [[206, 152], [93, 477]], 
* Val   accuracy / confusion: 72.37% / [[158, 72], [91, 269]]

------------------------------ Epoch 081 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.541968
- Iter 028 / 029, Loss: 0.505501

* Train accuracy / confusion: 74.57% / [[218, 146], [90, 474]], 
* Val   accuracy / confusion: 75.25% / [[126, 104], [42, 318]]

------------------------------ Epoch 082 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.493508
- Iter 028 / 029, Loss: 0.415831

* Train accuracy / confusion: 72.41% / [[211, 153], [103, 461]], 
* Val   accuracy / confusion: 67.80% / [[58, 172], [18, 342]]

------------------------------ Epoch 083 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.462394
- Iter 028 / 029, Loss: 0.599287

* Train accuracy / confusion: 74.03% / [[225, 142], [99, 462]], 
* Val   accuracy / confusion: 72.20% / [[151, 79], [85, 275]]

------------------------------ Epoch 084 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.644322
- Iter 028 / 029, Loss: 0.787935

* Train accuracy / confusion: 73.92% / [[207, 158], [84, 479]], 
* Val   accuracy / confusion: 73.73% / [[113, 117], [38, 322]]

------------------------------ Epoch 085 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.541229
- Iter 028 / 029, Loss: 0.489958

* Train accuracy / confusion: 73.49% / [[222, 143], [103, 460]], 
* Val   accuracy / confusion: 75.42% / [[136, 94], [51, 309]]

------------------------------ Epoch 086 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.529641
- Iter 028 / 029, Loss: 0.628777

* Train accuracy / confusion: 74.89% / [[218, 145], [88, 477]], 
* Val   accuracy / confusion: 75.59% / [[123, 107], [37, 323]]

------------------------------ Epoch 087 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.521479
- Iter 028 / 029, Loss: 0.528171

* Train accuracy / confusion: 76.51% / [[221, 138], [80, 489]], 
* Val   accuracy / confusion: 72.88% / [[159, 71], [89, 271]]

------------------------------ Epoch 088 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.592988
- Iter 028 / 029, Loss: 0.636709

* Train accuracy / confusion: 75.54% / [[237, 127], [100, 464]], 
* Val   accuracy / confusion: 74.07% / [[124, 106], [47, 313]]

------------------------------ Epoch 089 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.584388
- Iter 028 / 029, Loss: 0.657834

* Train accuracy / confusion: 74.78% / [[211, 146], [88, 483]], 
* Val   accuracy / confusion: 74.75% / [[117, 113], [36, 324]]

------------------------------ Epoch 090 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.448074
- Iter 028 / 029, Loss: 0.616627

* Train accuracy / confusion: 74.89% / [[232, 133], [100, 463]], 
* Val   accuracy / confusion: 69.83% / [[68, 162], [16, 344]]

------------------------------ Epoch 091 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.473617
- Iter 028 / 029, Loss: 0.705308

* Train accuracy / confusion: 74.03% / [[213, 151], [90, 474]], 
* Val   accuracy / confusion: 74.75% / [[129, 101], [48, 312]]

------------------------------ Epoch 092 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.702561
- Iter 028 / 029, Loss: 0.514702

* Train accuracy / confusion: 75.75% / [[230, 133], [92, 473]], 
* Val   accuracy / confusion: 75.76% / [[160, 70], [73, 287]]

------------------------------ Epoch 093 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.452088
- Iter 028 / 029, Loss: 0.663112

* Train accuracy / confusion: 76.72% / [[232, 126], [90, 480]], 
* Val   accuracy / confusion: 72.71% / [[144, 86], [75, 285]]

------------------------------ Epoch 094 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.397798
- Iter 028 / 029, Loss: 0.598966

* Train accuracy / confusion: 75.43% / [[229, 131], [97, 471]], 
* Val   accuracy / confusion: 74.41% / [[124, 106], [45, 315]]

------------------------------ Epoch 095 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.528986
- Iter 028 / 029, Loss: 0.426576

* Train accuracy / confusion: 73.81% / [[213, 150], [93, 472]], 
* Val   accuracy / confusion: 76.78% / [[141, 89], [48, 312]]

------------------------------ Epoch 096 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.419228
- Iter 028 / 029, Loss: 0.703874

* Train accuracy / confusion: 74.35% / [[220, 139], [99, 470]], 
* Val   accuracy / confusion: 75.76% / [[136, 94], [49, 311]]

------------------------------ Epoch 097 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.581888
- Iter 028 / 029, Loss: 0.648057

* Train accuracy / confusion: 73.28% / [[221, 145], [103, 459]], 
* Val   accuracy / confusion: 72.37% / [[170, 60], [103, 257]]

------------------------------ Epoch 098 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.347615
- Iter 028 / 029, Loss: 0.508826

* Train accuracy / confusion: 74.46% / [[225, 136], [101, 466]], 
* Val   accuracy / confusion: 75.25% / [[132, 98], [48, 312]]

------------------------------ Epoch 099 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.453874
- Iter 028 / 029, Loss: 0.447897

* Train accuracy / confusion: 74.89% / [[224, 143], [90, 471]], 
* Val   accuracy / confusion: 73.73% / [[108, 122], [33, 327]]

------------------------------ Epoch 100 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.673402
- Iter 028 / 029, Loss: 0.428906

* Train accuracy / confusion: 75.97% / [[240, 125], [98, 465]], 
* Val   accuracy / confusion: 72.20% / [[141, 89], [75, 285]]

------------------------------ Epoch 101 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.417550
- Iter 028 / 029, Loss: 0.629892

* Train accuracy / confusion: 75.22% / [[229, 132], [98, 469]], 
* Val   accuracy / confusion: 73.22% / [[134, 96], [62, 298]]

------------------------------ Epoch 102 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.406241
- Iter 028 / 029, Loss: 0.387004

* Train accuracy / confusion: 75.00% / [[233, 131], [101, 463]], 
* Val   accuracy / confusion: 72.71% / [[153, 77], [84, 276]]

------------------------------ Epoch 103 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.584851
- Iter 028 / 029, Loss: 0.613348

* Train accuracy / confusion: 76.40% / [[221, 138], [81, 488]], 
* Val   accuracy / confusion: 71.86% / [[166, 64], [102, 258]]

------------------------------ Epoch 104 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.591137
- Iter 028 / 029, Loss: 0.548778

* Train accuracy / confusion: 74.03% / [[219, 142], [99, 468]], 
* Val   accuracy / confusion: 75.25% / [[134, 96], [50, 310]]

------------------------------ Epoch 105 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.498538
- Iter 028 / 029, Loss: 0.399746

* Train accuracy / confusion: 73.92% / [[239, 122], [120, 447]], 
* Val   accuracy / confusion: 73.73% / [[151, 79], [76, 284]]

------------------------------ Epoch 106 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.576672
- Iter 028 / 029, Loss: 0.640240

* Train accuracy / confusion: 74.78% / [[220, 142], [92, 474]], 
* Val   accuracy / confusion: 75.25% / [[153, 77], [69, 291]]

------------------------------ Epoch 107 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.367399
- Iter 028 / 029, Loss: 0.459972

* Train accuracy / confusion: 76.62% / [[235, 128], [89, 476]], 
* Val   accuracy / confusion: 67.46% / [[94, 136], [56, 304]]

------------------------------ Epoch 108 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.643075
- Iter 028 / 029, Loss: 0.498396

* Train accuracy / confusion: 74.25% / [[212, 149], [90, 477]], 
* Val   accuracy / confusion: 72.37% / [[143, 87], [76, 284]]

------------------------------ Epoch 109 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.595578
- Iter 028 / 029, Loss: 0.659206

* Train accuracy / confusion: 76.72% / [[234, 130], [86, 478]], 
* Val   accuracy / confusion: 71.19% / [[144, 86], [84, 276]]

------------------------------ Epoch 110 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.619570
- Iter 028 / 029, Loss: 0.403229

* Train accuracy / confusion: 75.65% / [[237, 126], [100, 465]], 
* Val   accuracy / confusion: 71.69% / [[142, 88], [79, 281]]

------------------------------ Epoch 111 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.549087
- Iter 028 / 029, Loss: 0.457841

* Train accuracy / confusion: 76.83% / [[244, 119], [96, 469]], 
* Val   accuracy / confusion: 73.22% / [[142, 88], [70, 290]]

------------------------------ Epoch 112 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.638257
- Iter 028 / 029, Loss: 0.437356

* Train accuracy / confusion: 78.02% / [[240, 120], [84, 484]], 
* Val   accuracy / confusion: 76.10% / [[165, 65], [76, 284]]

------------------------------ Epoch 113 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.381537
- Iter 028 / 029, Loss: 0.432886

* Train accuracy / confusion: 76.40% / [[241, 122], [97, 468]], 
* Val   accuracy / confusion: 72.54% / [[138, 92], [70, 290]]

------------------------------ Epoch 114 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.416929
- Iter 028 / 029, Loss: 0.442803

* Train accuracy / confusion: 76.72% / [[236, 124], [92, 476]], 
* Val   accuracy / confusion: 73.73% / [[140, 90], [65, 295]]

------------------------------ Epoch 115 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.464661
- Iter 028 / 029, Loss: 0.424003

* Train accuracy / confusion: 76.08% / [[239, 121], [101, 467]], 
* Val   accuracy / confusion: 68.47% / [[172, 58], [128, 232]]

------------------------------ Epoch 116 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.451057
- Iter 028 / 029, Loss: 0.377921

* Train accuracy / confusion: 77.26% / [[230, 132], [79, 487]], 
* Val   accuracy / confusion: 75.08% / [[135, 95], [52, 308]]

------------------------------ Epoch 117 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.472479
- Iter 028 / 029, Loss: 0.433365

* Train accuracy / confusion: 75.75% / [[224, 137], [88, 479]], 
* Val   accuracy / confusion: 70.34% / [[94, 136], [39, 321]]

------------------------------ Epoch 118 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.435057
- Iter 028 / 029, Loss: 0.380065

* Train accuracy / confusion: 77.59% / [[244, 116], [92, 476]], 
* Val   accuracy / confusion: 70.00% / [[154, 76], [101, 259]]

------------------------------ Epoch 119 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.560581
- Iter 028 / 029, Loss: 0.461839

* Train accuracy / confusion: 77.05% / [[236, 122], [91, 479]], 
* Val   accuracy / confusion: 74.41% / [[160, 70], [81, 279]]

------------------------------ Epoch 120 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.506981
- Iter 028 / 029, Loss: 0.402535

* Train accuracy / confusion: 76.51% / [[239, 121], [97, 471]], 
* Val   accuracy / confusion: 73.05% / [[129, 101], [58, 302]]

------------------------------ Epoch 121 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.483489
- Iter 028 / 029, Loss: 0.401900

* Train accuracy / confusion: 75.75% / [[227, 137], [88, 476]], 
* Val   accuracy / confusion: 72.88% / [[91, 139], [21, 339]]

------------------------------ Epoch 122 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.705050
- Iter 028 / 029, Loss: 0.695003

* Train accuracy / confusion: 76.72% / [[240, 120], [96, 472]], 
* Val   accuracy / confusion: 71.86% / [[113, 117], [49, 311]]

------------------------------ Epoch 123 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.508961
- Iter 028 / 029, Loss: 0.570640

* Train accuracy / confusion: 76.19% / [[223, 138], [83, 484]], 
* Val   accuracy / confusion: 76.78% / [[158, 72], [65, 295]]

------------------------------ Epoch 124 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.772940
- Iter 028 / 029, Loss: 0.424419

* Train accuracy / confusion: 76.94% / [[233, 129], [85, 481]], 
* Val   accuracy / confusion: 70.68% / [[119, 111], [62, 298]]

------------------------------ Epoch 125 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.500803
- Iter 028 / 029, Loss: 0.727352

* Train accuracy / confusion: 77.48% / [[241, 117], [92, 478]], 
* Val   accuracy / confusion: 73.22% / [[117, 113], [45, 315]]

------------------------------ Epoch 126 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.620007
- Iter 028 / 029, Loss: 0.403944

* Train accuracy / confusion: 78.02% / [[233, 129], [75, 491]], 
* Val   accuracy / confusion: 70.34% / [[180, 50], [125, 235]]

------------------------------ Epoch 127 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.478410
- Iter 028 / 029, Loss: 0.587248

* Train accuracy / confusion: 77.16% / [[231, 126], [86, 485]], 
* Val   accuracy / confusion: 73.56% / [[127, 103], [53, 307]]

------------------------------ Epoch 128 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.561236
- Iter 028 / 029, Loss: 0.339489

* Train accuracy / confusion: 76.40% / [[235, 128], [91, 474]], 
* Val   accuracy / confusion: 74.41% / [[133, 97], [54, 306]]

------------------------------ Epoch 129 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.605398
- Iter 028 / 029, Loss: 0.425757

* Train accuracy / confusion: 78.02% / [[236, 127], [77, 488]], 
* Val   accuracy / confusion: 74.07% / [[158, 72], [81, 279]]

------------------------------ Epoch 130 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.560980
- Iter 028 / 029, Loss: 0.533306

* Train accuracy / confusion: 77.26% / [[238, 124], [87, 479]], 
* Val   accuracy / confusion: 74.58% / [[137, 93], [57, 303]]

------------------------------ Epoch 131 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.528121
- Iter 028 / 029, Loss: 0.417626

* Train accuracy / confusion: 78.02% / [[250, 111], [93, 474]], 
* Val   accuracy / confusion: 73.56% / [[124, 106], [50, 310]]

------------------------------ Epoch 132 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.583281
- Iter 028 / 029, Loss: 0.490941

* Train accuracy / confusion: 76.08% / [[217, 146], [76, 489]], 
* Val   accuracy / confusion: 77.63% / [[149, 81], [51, 309]]

------------------------------ Epoch 133 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.581132
- Iter 028 / 029, Loss: 0.451915

* Train accuracy / confusion: 76.40% / [[230, 131], [88, 479]], 
* Val   accuracy / confusion: 73.90% / [[138, 92], [62, 298]]

------------------------------ Epoch 134 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.331982
- Iter 028 / 029, Loss: 0.510301

* Train accuracy / confusion: 76.62% / [[236, 121], [96, 475]], 
* Val   accuracy / confusion: 73.05% / [[119, 111], [48, 312]]

------------------------------ Epoch 135 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.395582
- Iter 028 / 029, Loss: 0.413488

* Train accuracy / confusion: 78.56% / [[251, 114], [85, 478]], 
* Val   accuracy / confusion: 73.39% / [[148, 82], [75, 285]]

------------------------------ Epoch 136 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.722721
- Iter 028 / 029, Loss: 0.455595

* Train accuracy / confusion: 75.86% / [[224, 139], [85, 480]], 
* Val   accuracy / confusion: 75.42% / [[126, 104], [41, 319]]

------------------------------ Epoch 137 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.439782
- Iter 028 / 029, Loss: 0.526382

* Train accuracy / confusion: 78.23% / [[240, 120], [82, 486]], 
* Val   accuracy / confusion: 74.41% / [[126, 104], [47, 313]]

------------------------------ Epoch 138 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.615071
- Iter 028 / 029, Loss: 0.471314

* Train accuracy / confusion: 76.40% / [[239, 124], [95, 470]], 
* Val   accuracy / confusion: 75.25% / [[149, 81], [65, 295]]

------------------------------ Epoch 139 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.384660
- Iter 028 / 029, Loss: 0.476763

* Train accuracy / confusion: 77.16% / [[241, 121], [91, 475]], 
* Val   accuracy / confusion: 73.56% / [[141, 89], [67, 293]]

------------------------------ Epoch 140 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.336796
- Iter 028 / 029, Loss: 0.468942

* Train accuracy / confusion: 77.48% / [[240, 119], [90, 479]], 
* Val   accuracy / confusion: 75.42% / [[136, 94], [51, 309]]

------------------------------ Epoch 141 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.495659
- Iter 028 / 029, Loss: 0.475402

* Train accuracy / confusion: 77.59% / [[231, 130], [78, 489]], 
* Val   accuracy / confusion: 74.41% / [[151, 79], [72, 288]]

------------------------------ Epoch 142 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.609001
- Iter 028 / 029, Loss: 0.441535

* Train accuracy / confusion: 77.05% / [[238, 123], [90, 477]], 
* Val   accuracy / confusion: 72.88% / [[115, 115], [45, 315]]

------------------------------ Epoch 143 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.348874
- Iter 028 / 029, Loss: 0.384617

* Train accuracy / confusion: 76.29% / [[225, 132], [88, 483]], 
* Val   accuracy / confusion: 73.73% / [[145, 85], [70, 290]]

------------------------------ Epoch 144 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.448006
- Iter 028 / 029, Loss: 0.684431

* Train accuracy / confusion: 77.69% / [[241, 120], [87, 480]], 
* Val   accuracy / confusion: 72.03% / [[94, 136], [29, 331]]

------------------------------ Epoch 145 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.534127
- Iter 028 / 029, Loss: 0.647616

* Train accuracy / confusion: 76.83% / [[242, 118], [97, 471]], 
* Val   accuracy / confusion: 75.42% / [[137, 93], [52, 308]]

------------------------------ Epoch 146 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.424306
- Iter 028 / 029, Loss: 0.507340

* Train accuracy / confusion: 78.23% / [[245, 116], [86, 481]], 
* Val   accuracy / confusion: 74.07% / [[141, 89], [64, 296]]

------------------------------ Epoch 147 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.408590
- Iter 028 / 029, Loss: 0.452348

* Train accuracy / confusion: 76.08% / [[236, 125], [97, 470]], 
* Val   accuracy / confusion: 73.56% / [[157, 73], [83, 277]]

------------------------------ Epoch 148 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.485251
- Iter 028 / 029, Loss: 0.405035

* Train accuracy / confusion: 78.34% / [[248, 116], [85, 479]], 
* Val   accuracy / confusion: 73.39% / [[122, 108], [49, 311]]

------------------------------ Epoch 149 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.540212
- Iter 028 / 029, Loss: 0.571141

* Train accuracy / confusion: 76.29% / [[232, 135], [85, 476]], 
* Val   accuracy / confusion: 75.42% / [[118, 112], [33, 327]]

------------------------------ Epoch 150 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.444837
- Iter 028 / 029, Loss: 0.412720

* Train accuracy / confusion: 78.66% / [[243, 116], [82, 487]], 
* Val   accuracy / confusion: 72.54% / [[105, 125], [37, 323]]

------------------------------ Epoch 151 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.370250
- Iter 028 / 029, Loss: 0.552607

* Train accuracy / confusion: 78.02% / [[252, 111], [93, 472]], 
* Val   accuracy / confusion: 74.41% / [[134, 96], [55, 305]]

------------------------------ Epoch 152 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.361072
- Iter 028 / 029, Loss: 0.740761

* Train accuracy / confusion: 77.69% / [[247, 116], [91, 474]], 
* Val   accuracy / confusion: 74.41% / [[159, 71], [80, 280]]

------------------------------ Epoch 153 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.372104
- Iter 028 / 029, Loss: 0.656934

* Train accuracy / confusion: 77.37% / [[247, 114], [96, 471]], 
* Val   accuracy / confusion: 74.92% / [[125, 105], [43, 317]]

------------------------------ Epoch 154 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.366243
- Iter 028 / 029, Loss: 0.404189

* Train accuracy / confusion: 78.45% / [[255, 109], [91, 473]], 
* Val   accuracy / confusion: 67.63% / [[71, 159], [32, 328]]

------------------------------ Epoch 155 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.298185
- Iter 028 / 029, Loss: 0.623718

* Train accuracy / confusion: 78.77% / [[248, 110], [87, 483]], 
* Val   accuracy / confusion: 73.73% / [[154, 76], [79, 281]]

------------------------------ Epoch 156 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.471416
- Iter 028 / 029, Loss: 0.548182

* Train accuracy / confusion: 76.40% / [[240, 125], [94, 469]], 
* Val   accuracy / confusion: 73.56% / [[147, 83], [73, 287]]

------------------------------ Epoch 157 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.489675
- Iter 028 / 029, Loss: 0.449068

* Train accuracy / confusion: 77.69% / [[249, 113], [94, 472]], 
* Val   accuracy / confusion: 71.53% / [[164, 66], [102, 258]]

------------------------------ Epoch 158 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.469806
- Iter 028 / 029, Loss: 0.592261

* Train accuracy / confusion: 76.29% / [[231, 132], [88, 477]], 
* Val   accuracy / confusion: 74.24% / [[110, 120], [32, 328]]

------------------------------ Epoch 159 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.362752
- Iter 028 / 029, Loss: 0.464650

* Train accuracy / confusion: 76.94% / [[235, 130], [84, 479]], 
* Val   accuracy / confusion: 74.58% / [[131, 99], [51, 309]]

------------------------------ Epoch 160 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.511036
- Iter 028 / 029, Loss: 0.282708

* Train accuracy / confusion: 80.28% / [[266, 95], [88, 479]], 
* Val   accuracy / confusion: 73.56% / [[123, 107], [49, 311]]

------------------------------ Epoch 161 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.509213
- Iter 028 / 029, Loss: 0.305244

* Train accuracy / confusion: 77.26% / [[228, 133], [78, 489]], 
* Val   accuracy / confusion: 72.88% / [[120, 110], [50, 310]]

------------------------------ Epoch 162 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.455242
- Iter 028 / 029, Loss: 0.379976

* Train accuracy / confusion: 78.77% / [[236, 124], [73, 495]], 
* Val   accuracy / confusion: 71.19% / [[153, 77], [93, 267]]

------------------------------ Epoch 163 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.374814
- Iter 028 / 029, Loss: 0.312493

* Train accuracy / confusion: 77.91% / [[245, 118], [87, 478]], 
* Val   accuracy / confusion: 71.19% / [[171, 59], [111, 249]]

------------------------------ Epoch 164 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.457238
- Iter 028 / 029, Loss: 0.382112

* Train accuracy / confusion: 77.80% / [[240, 122], [84, 482]], 
* Val   accuracy / confusion: 73.56% / [[143, 87], [69, 291]]

------------------------------ Epoch 165 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.569810
- Iter 028 / 029, Loss: 0.416103

* Train accuracy / confusion: 77.16% / [[235, 123], [89, 481]], 
* Val   accuracy / confusion: 76.10% / [[134, 96], [45, 315]]

------------------------------ Epoch 166 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.471684
- Iter 028 / 029, Loss: 0.411750

* Train accuracy / confusion: 77.80% / [[235, 129], [77, 487]], 
* Val   accuracy / confusion: 73.73% / [[146, 84], [71, 289]]

------------------------------ Epoch 167 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.535820
- Iter 028 / 029, Loss: 0.384668

* Train accuracy / confusion: 78.23% / [[247, 116], [86, 479]], 
* Val   accuracy / confusion: 72.03% / [[147, 83], [82, 278]]

------------------------------ Epoch 168 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.460160
- Iter 028 / 029, Loss: 0.660992

* Train accuracy / confusion: 78.77% / [[253, 112], [85, 478]], 
* Val   accuracy / confusion: 75.25% / [[174, 56], [90, 270]]

------------------------------ Epoch 169 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.403696
- Iter 028 / 029, Loss: 0.424048

* Train accuracy / confusion: 77.69% / [[243, 119], [88, 478]], 
* Val   accuracy / confusion: 74.75% / [[158, 72], [77, 283]]

------------------------------ Epoch 170 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.548367
- Iter 028 / 029, Loss: 0.270638

* Train accuracy / confusion: 78.66% / [[253, 109], [89, 477]], 
* Val   accuracy / confusion: 73.90% / [[124, 106], [48, 312]]

------------------------------ Epoch 171 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.525249
- Iter 028 / 029, Loss: 0.526564

* Train accuracy / confusion: 77.91% / [[254, 108], [97, 469]], 
* Val   accuracy / confusion: 75.08% / [[119, 111], [36, 324]]

------------------------------ Epoch 172 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.556750
- Iter 028 / 029, Loss: 0.479291

* Train accuracy / confusion: 77.69% / [[245, 116], [91, 476]], 
* Val   accuracy / confusion: 73.39% / [[173, 57], [100, 260]]

------------------------------ Epoch 173 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.677837
- Iter 028 / 029, Loss: 0.472429

* Train accuracy / confusion: 78.45% / [[262, 101], [99, 466]], 
* Val   accuracy / confusion: 76.44% / [[146, 84], [55, 305]]

------------------------------ Epoch 174 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.367366
- Iter 028 / 029, Loss: 0.396452

* Train accuracy / confusion: 77.48% / [[243, 119], [90, 476]], 
* Val   accuracy / confusion: 72.03% / [[167, 63], [102, 258]]

------------------------------ Epoch 175 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.517922
- Iter 028 / 029, Loss: 0.492286

* Train accuracy / confusion: 77.91% / [[249, 111], [94, 474]], 
* Val   accuracy / confusion: 73.39% / [[132, 98], [59, 301]]

------------------------------ Epoch 176 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.351309
- Iter 028 / 029, Loss: 0.434487

* Train accuracy / confusion: 77.59% / [[241, 120], [88, 479]], 
* Val   accuracy / confusion: 73.05% / [[190, 40], [119, 241]]

------------------------------ Epoch 177 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.591432
- Iter 028 / 029, Loss: 0.325661

* Train accuracy / confusion: 78.23% / [[251, 109], [93, 475]], 
* Val   accuracy / confusion: 74.41% / [[142, 88], [63, 297]]

------------------------------ Epoch 178 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.477586
- Iter 028 / 029, Loss: 0.403228

* Train accuracy / confusion: 76.83% / [[234, 127], [88, 479]], 
* Val   accuracy / confusion: 70.68% / [[134, 96], [77, 283]]

------------------------------ Epoch 179 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.326953
- Iter 028 / 029, Loss: 0.604462

* Train accuracy / confusion: 78.02% / [[255, 106], [98, 469]], 
* Val   accuracy / confusion: 71.69% / [[93, 137], [30, 330]]

------------------------------ Epoch 180 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.467487
- Iter 028 / 029, Loss: 0.491397

* Train accuracy / confusion: 79.31% / [[254, 110], [82, 482]], 
* Val   accuracy / confusion: 76.61% / [[145, 85], [53, 307]]

------------------------------ Epoch 181 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.673740
- Iter 028 / 029, Loss: 0.394626

* Train accuracy / confusion: 79.63% / [[268, 96], [93, 471]], 
* Val   accuracy / confusion: 71.19% / [[162, 68], [102, 258]]

------------------------------ Epoch 182 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.565780
- Iter 028 / 029, Loss: 0.494939

* Train accuracy / confusion: 78.23% / [[252, 107], [95, 474]], 
* Val   accuracy / confusion: 73.73% / [[110, 120], [35, 325]]

------------------------------ Epoch 183 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.419849
- Iter 028 / 029, Loss: 0.569889

* Train accuracy / confusion: 79.09% / [[244, 119], [75, 490]], 
* Val   accuracy / confusion: 72.03% / [[129, 101], [64, 296]]

------------------------------ Epoch 184 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.512066
- Iter 028 / 029, Loss: 0.369984

* Train accuracy / confusion: 78.66% / [[253, 112], [86, 477]], 
* Val   accuracy / confusion: 73.90% / [[151, 79], [75, 285]]

------------------------------ Epoch 185 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.452613
- Iter 028 / 029, Loss: 0.394745

* Train accuracy / confusion: 79.31% / [[246, 114], [78, 490]], 
* Val   accuracy / confusion: 72.37% / [[142, 88], [75, 285]]

------------------------------ Epoch 186 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.416434
- Iter 028 / 029, Loss: 0.408035

* Train accuracy / confusion: 78.66% / [[248, 114], [84, 482]], 
* Val   accuracy / confusion: 73.56% / [[130, 100], [56, 304]]

------------------------------ Epoch 187 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.482336
- Iter 028 / 029, Loss: 0.664454

* Train accuracy / confusion: 78.77% / [[249, 112], [85, 482]], 
* Val   accuracy / confusion: 73.22% / [[145, 85], [73, 287]]

------------------------------ Epoch 188 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.504960
- Iter 028 / 029, Loss: 0.496913

* Train accuracy / confusion: 77.26% / [[242, 120], [91, 475]], 
* Val   accuracy / confusion: 73.22% / [[108, 122], [36, 324]]

------------------------------ Epoch 189 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.396150
- Iter 028 / 029, Loss: 0.589513

* Train accuracy / confusion: 77.69% / [[249, 112], [95, 472]], 
* Val   accuracy / confusion: 74.24% / [[128, 102], [50, 310]]

------------------------------ Epoch 190 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.604021
- Iter 028 / 029, Loss: 0.472241

* Train accuracy / confusion: 77.69% / [[238, 127], [80, 483]], 
* Val   accuracy / confusion: 74.41% / [[142, 88], [63, 297]]

------------------------------ Epoch 191 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.397967
- Iter 028 / 029, Loss: 0.489856

* Train accuracy / confusion: 77.26% / [[253, 107], [104, 464]], 
* Val   accuracy / confusion: 75.25% / [[148, 82], [64, 296]]

------------------------------ Epoch 192 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.528833
- Iter 028 / 029, Loss: 0.434606

* Train accuracy / confusion: 78.66% / [[236, 126], [72, 494]], 
* Val   accuracy / confusion: 72.54% / [[121, 109], [53, 307]]

------------------------------ Epoch 193 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.619281
- Iter 028 / 029, Loss: 0.500056

* Train accuracy / confusion: 78.88% / [[254, 107], [89, 478]], 
* Val   accuracy / confusion: 70.85% / [[175, 55], [117, 243]]

------------------------------ Epoch 194 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.347188
- Iter 028 / 029, Loss: 0.475800

* Train accuracy / confusion: 76.51% / [[244, 123], [95, 466]], 
* Val   accuracy / confusion: 74.07% / [[120, 110], [43, 317]]

------------------------------ Epoch 195 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.394905
- Iter 028 / 029, Loss: 0.565647

* Train accuracy / confusion: 79.42% / [[265, 99], [92, 472]], 
* Val   accuracy / confusion: 71.53% / [[138, 92], [76, 284]]

------------------------------ Epoch 196 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.558701
- Iter 028 / 029, Loss: 0.355482

* Train accuracy / confusion: 78.45% / [[236, 126], [74, 492]], 
* Val   accuracy / confusion: 71.86% / [[122, 108], [58, 302]]

------------------------------ Epoch 197 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.383869
- Iter 028 / 029, Loss: 0.513819

* Train accuracy / confusion: 79.85% / [[250, 111], [76, 491]], 
* Val   accuracy / confusion: 74.58% / [[133, 97], [53, 307]]

------------------------------ Epoch 198 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.596919
- Iter 028 / 029, Loss: 0.424546

* Train accuracy / confusion: 78.56% / [[241, 118], [81, 488]], 
* Val   accuracy / confusion: 72.71% / [[148, 82], [79, 281]]

------------------------------ Epoch 199 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.419300
- Iter 028 / 029, Loss: 0.313507

* Train accuracy / confusion: 78.99% / [[246, 114], [81, 487]], 
* Val   accuracy / confusion: 71.69% / [[98, 132], [35, 325]]

------------------------------ Epoch 200 / 500, Learning rate: 2.75e-03 ------------------------------
- Iter 014 / 029, Loss: 0.330821
- Iter 028 / 029, Loss: 0.716350

* Train accuracy / confusion: 78.77% / [[251, 112], [85, 480]], 
* Val   accuracy / confusion: 74.75% / [[139, 91], [58, 302]]

------------------------------ Epoch 201 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.497844
- Iter 028 / 029, Loss: 0.434931

* Train accuracy / confusion: 79.53% / [[243, 117], [73, 495]], 
* Val   accuracy / confusion: 74.92% / [[130, 100], [48, 312]]

------------------------------ Epoch 202 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.293996
- Iter 028 / 029, Loss: 0.660517

* Train accuracy / confusion: 80.60% / [[250, 116], [64, 498]], 
* Val   accuracy / confusion: 73.39% / [[133, 97], [60, 300]]

------------------------------ Epoch 203 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.475512
- Iter 028 / 029, Loss: 0.481828

* Train accuracy / confusion: 79.74% / [[250, 113], [75, 490]], 
* Val   accuracy / confusion: 73.73% / [[134, 96], [59, 301]]

------------------------------ Epoch 204 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.413217
- Iter 028 / 029, Loss: 0.454396

* Train accuracy / confusion: 77.48% / [[237, 122], [87, 482]], 
* Val   accuracy / confusion: 72.71% / [[134, 96], [65, 295]]

------------------------------ Epoch 205 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.442066
- Iter 028 / 029, Loss: 0.426826

* Train accuracy / confusion: 80.50% / [[254, 109], [72, 493]], 
* Val   accuracy / confusion: 74.75% / [[122, 108], [41, 319]]

------------------------------ Epoch 206 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.395565
- Iter 028 / 029, Loss: 0.428691

* Train accuracy / confusion: 80.82% / [[252, 109], [69, 498]], 
* Val   accuracy / confusion: 73.73% / [[138, 92], [63, 297]]

------------------------------ Epoch 207 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.297401
- Iter 028 / 029, Loss: 0.446413

* Train accuracy / confusion: 77.91% / [[237, 127], [78, 486]], 
* Val   accuracy / confusion: 73.56% / [[135, 95], [61, 299]]

------------------------------ Epoch 208 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.337365
- Iter 028 / 029, Loss: 0.634970

* Train accuracy / confusion: 79.53% / [[253, 111], [79, 485]], 
* Val   accuracy / confusion: 73.73% / [[136, 94], [61, 299]]

------------------------------ Epoch 209 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.287147
- Iter 028 / 029, Loss: 0.414288

* Train accuracy / confusion: 80.17% / [[256, 106], [78, 488]], 
* Val   accuracy / confusion: 74.75% / [[144, 86], [63, 297]]

------------------------------ Epoch 210 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.430025
- Iter 028 / 029, Loss: 0.413695

* Train accuracy / confusion: 80.82% / [[255, 107], [71, 495]], 
* Val   accuracy / confusion: 72.37% / [[134, 96], [67, 293]]

------------------------------ Epoch 211 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.340724
- Iter 028 / 029, Loss: 0.338228

* Train accuracy / confusion: 80.60% / [[255, 106], [74, 493]], 
* Val   accuracy / confusion: 72.88% / [[141, 89], [71, 289]]

------------------------------ Epoch 212 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.456886
- Iter 028 / 029, Loss: 0.436284

* Train accuracy / confusion: 79.42% / [[251, 112], [79, 486]], 
* Val   accuracy / confusion: 71.36% / [[127, 103], [66, 294]]

------------------------------ Epoch 213 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.517967
- Iter 028 / 029, Loss: 0.422324

* Train accuracy / confusion: 80.06% / [[253, 109], [76, 490]], 
* Val   accuracy / confusion: 73.39% / [[130, 100], [57, 303]]

------------------------------ Epoch 214 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.565128
- Iter 028 / 029, Loss: 0.371108

* Train accuracy / confusion: 79.63% / [[254, 108], [81, 485]], 
* Val   accuracy / confusion: 71.69% / [[133, 97], [70, 290]]

------------------------------ Epoch 215 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.321977
- Iter 028 / 029, Loss: 0.255224

* Train accuracy / confusion: 79.42% / [[246, 115], [76, 491]], 
* Val   accuracy / confusion: 73.56% / [[134, 96], [60, 300]]

------------------------------ Epoch 216 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.408022
- Iter 028 / 029, Loss: 0.672179

* Train accuracy / confusion: 79.85% / [[255, 109], [78, 486]], 
* Val   accuracy / confusion: 74.41% / [[141, 89], [62, 298]]

------------------------------ Epoch 217 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.412292
- Iter 028 / 029, Loss: 0.502716

* Train accuracy / confusion: 80.71% / [[259, 102], [77, 490]], 
* Val   accuracy / confusion: 71.53% / [[128, 102], [66, 294]]

------------------------------ Epoch 218 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.489903
- Iter 028 / 029, Loss: 0.538449

* Train accuracy / confusion: 80.17% / [[247, 114], [70, 497]], 
* Val   accuracy / confusion: 71.53% / [[133, 97], [71, 289]]

------------------------------ Epoch 219 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.475273
- Iter 028 / 029, Loss: 0.417306

* Train accuracy / confusion: 79.63% / [[250, 112], [77, 489]], 
* Val   accuracy / confusion: 72.03% / [[123, 107], [58, 302]]

------------------------------ Epoch 220 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.384135
- Iter 028 / 029, Loss: 0.405227

* Train accuracy / confusion: 81.79% / [[261, 100], [69, 498]], 
* Val   accuracy / confusion: 72.54% / [[135, 95], [67, 293]]

------------------------------ Epoch 221 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.335834
- Iter 028 / 029, Loss: 0.543697

* Train accuracy / confusion: 80.06% / [[251, 111], [74, 492]], 
* Val   accuracy / confusion: 73.56% / [[137, 93], [63, 297]]

------------------------------ Epoch 222 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.415667
- Iter 028 / 029, Loss: 0.580464

* Train accuracy / confusion: 79.74% / [[250, 116], [72, 490]], 
* Val   accuracy / confusion: 72.88% / [[139, 91], [69, 291]]

------------------------------ Epoch 223 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.304027
- Iter 028 / 029, Loss: 0.382554

* Train accuracy / confusion: 80.93% / [[260, 101], [76, 491]], 
* Val   accuracy / confusion: 73.22% / [[145, 85], [73, 287]]

------------------------------ Epoch 224 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.422501
- Iter 028 / 029, Loss: 0.696684

* Train accuracy / confusion: 80.28% / [[253, 106], [77, 492]], 
* Val   accuracy / confusion: 72.88% / [[139, 91], [69, 291]]

------------------------------ Epoch 225 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.436782
- Iter 028 / 029, Loss: 0.583620

* Train accuracy / confusion: 80.17% / [[250, 112], [72, 494]], 
* Val   accuracy / confusion: 72.88% / [[145, 85], [75, 285]]

------------------------------ Epoch 226 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.322988
- Iter 028 / 029, Loss: 0.347303

* Train accuracy / confusion: 79.74% / [[251, 105], [83, 489]], 
* Val   accuracy / confusion: 73.39% / [[132, 98], [59, 301]]

------------------------------ Epoch 227 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.305937
- Iter 028 / 029, Loss: 0.296927

* Train accuracy / confusion: 80.39% / [[260, 103], [79, 486]], 
* Val   accuracy / confusion: 72.88% / [[133, 97], [63, 297]]

------------------------------ Epoch 228 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.339458
- Iter 028 / 029, Loss: 0.417303

* Train accuracy / confusion: 79.74% / [[257, 107], [81, 483]], 
* Val   accuracy / confusion: 72.54% / [[133, 97], [65, 295]]

------------------------------ Epoch 229 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.481209
- Iter 028 / 029, Loss: 0.354556

* Train accuracy / confusion: 79.20% / [[256, 107], [86, 479]], 
* Val   accuracy / confusion: 73.90% / [[144, 86], [68, 292]]

------------------------------ Epoch 230 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.288418
- Iter 028 / 029, Loss: 0.539193

* Train accuracy / confusion: 78.99% / [[250, 113], [82, 483]], 
* Val   accuracy / confusion: 73.22% / [[149, 81], [77, 283]]

------------------------------ Epoch 231 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.295259
- Iter 028 / 029, Loss: 0.420586

* Train accuracy / confusion: 81.57% / [[263, 100], [71, 494]], 
* Val   accuracy / confusion: 69.66% / [[122, 108], [71, 289]]

------------------------------ Epoch 232 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.303591
- Iter 028 / 029, Loss: 0.483818

* Train accuracy / confusion: 81.36% / [[264, 97], [76, 491]], 
* Val   accuracy / confusion: 71.36% / [[133, 97], [72, 288]]

------------------------------ Epoch 233 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.261111
- Iter 028 / 029, Loss: 0.301642

* Train accuracy / confusion: 80.60% / [[257, 102], [78, 491]], 
* Val   accuracy / confusion: 75.25% / [[141, 89], [57, 303]]

------------------------------ Epoch 234 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.293958
- Iter 028 / 029, Loss: 0.302030

* Train accuracy / confusion: 80.93% / [[255, 107], [70, 496]], 
* Val   accuracy / confusion: 70.68% / [[128, 102], [71, 289]]

------------------------------ Epoch 235 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.548640
- Iter 028 / 029, Loss: 0.368967

* Train accuracy / confusion: 79.31% / [[254, 107], [85, 482]], 
* Val   accuracy / confusion: 73.39% / [[140, 90], [67, 293]]

------------------------------ Epoch 236 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.368450
- Iter 028 / 029, Loss: 0.562543

* Train accuracy / confusion: 81.36% / [[261, 101], [72, 494]], 
* Val   accuracy / confusion: 71.19% / [[135, 95], [75, 285]]

------------------------------ Epoch 237 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.581676
- Iter 028 / 029, Loss: 0.323653

* Train accuracy / confusion: 80.50% / [[258, 105], [76, 489]], 
* Val   accuracy / confusion: 73.22% / [[134, 96], [62, 298]]

------------------------------ Epoch 238 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.342460
- Iter 028 / 029, Loss: 0.580279

* Train accuracy / confusion: 78.88% / [[247, 113], [83, 485]], 
* Val   accuracy / confusion: 71.86% / [[129, 101], [65, 295]]

------------------------------ Epoch 239 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.423511
- Iter 028 / 029, Loss: 0.574282

* Train accuracy / confusion: 80.39% / [[258, 103], [79, 488]], 
* Val   accuracy / confusion: 73.56% / [[143, 87], [69, 291]]

------------------------------ Epoch 240 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.403400
- Iter 028 / 029, Loss: 0.425950

* Train accuracy / confusion: 79.74% / [[254, 111], [77, 486]], 
* Val   accuracy / confusion: 72.54% / [[132, 98], [64, 296]]

------------------------------ Epoch 241 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.483575
- Iter 028 / 029, Loss: 0.463714

* Train accuracy / confusion: 79.31% / [[251, 109], [83, 485]], 
* Val   accuracy / confusion: 73.56% / [[136, 94], [62, 298]]

------------------------------ Epoch 242 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.424317
- Iter 028 / 029, Loss: 0.366792

* Train accuracy / confusion: 81.47% / [[261, 104], [68, 495]], 
* Val   accuracy / confusion: 71.69% / [[127, 103], [64, 296]]

------------------------------ Epoch 243 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.369160
- Iter 028 / 029, Loss: 0.330990

* Train accuracy / confusion: 82.00% / [[266, 99], [68, 495]], 
* Val   accuracy / confusion: 72.20% / [[133, 97], [67, 293]]

------------------------------ Epoch 244 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.618119
- Iter 028 / 029, Loss: 0.324272

* Train accuracy / confusion: 78.99% / [[248, 118], [77, 485]], 
* Val   accuracy / confusion: 72.37% / [[135, 95], [68, 292]]

------------------------------ Epoch 245 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.586996
- Iter 028 / 029, Loss: 0.566326

* Train accuracy / confusion: 79.85% / [[253, 109], [78, 488]], 
* Val   accuracy / confusion: 71.19% / [[142, 88], [82, 278]]

------------------------------ Epoch 246 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.598151
- Iter 028 / 029, Loss: 0.353398

* Train accuracy / confusion: 79.85% / [[252, 112], [75, 489]], 
* Val   accuracy / confusion: 71.86% / [[144, 86], [80, 280]]

------------------------------ Epoch 247 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.408496
- Iter 028 / 029, Loss: 0.456178

* Train accuracy / confusion: 79.96% / [[255, 106], [80, 487]], 
* Val   accuracy / confusion: 72.37% / [[140, 90], [73, 287]]

------------------------------ Epoch 248 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.309713
- Iter 028 / 029, Loss: 0.420113

* Train accuracy / confusion: 81.79% / [[257, 105], [64, 502]], 
* Val   accuracy / confusion: 72.88% / [[128, 102], [58, 302]]

------------------------------ Epoch 249 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.493357
- Iter 028 / 029, Loss: 0.322164

* Train accuracy / confusion: 81.57% / [[262, 98], [73, 495]], 
* Val   accuracy / confusion: 73.56% / [[139, 91], [65, 295]]

------------------------------ Epoch 250 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.352883
- Iter 028 / 029, Loss: 0.553026

* Train accuracy / confusion: 80.82% / [[255, 105], [73, 495]], 
* Val   accuracy / confusion: 73.05% / [[137, 93], [66, 294]]

------------------------------ Epoch 251 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.449805
- Iter 028 / 029, Loss: 0.457922

* Train accuracy / confusion: 81.14% / [[258, 102], [73, 495]], 
* Val   accuracy / confusion: 72.37% / [[140, 90], [73, 287]]

------------------------------ Epoch 252 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.584821
- Iter 028 / 029, Loss: 0.398020

* Train accuracy / confusion: 81.68% / [[264, 97], [73, 494]], 
* Val   accuracy / confusion: 75.42% / [[147, 83], [62, 298]]

------------------------------ Epoch 253 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.310453
- Iter 028 / 029, Loss: 0.313847

* Train accuracy / confusion: 79.96% / [[259, 108], [78, 483]], 
* Val   accuracy / confusion: 72.20% / [[132, 98], [66, 294]]

------------------------------ Epoch 254 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.486276
- Iter 028 / 029, Loss: 0.405329

* Train accuracy / confusion: 81.90% / [[264, 98], [70, 496]], 
* Val   accuracy / confusion: 70.00% / [[127, 103], [74, 286]]

------------------------------ Epoch 255 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.386976
- Iter 028 / 029, Loss: 0.460820

* Train accuracy / confusion: 81.14% / [[257, 107], [68, 496]], 
* Val   accuracy / confusion: 72.20% / [[139, 91], [73, 287]]

------------------------------ Epoch 256 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.273080
- Iter 028 / 029, Loss: 0.435536

* Train accuracy / confusion: 81.47% / [[263, 98], [74, 493]], 
* Val   accuracy / confusion: 74.41% / [[137, 93], [58, 302]]

------------------------------ Epoch 257 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.403889
- Iter 028 / 029, Loss: 0.587358

* Train accuracy / confusion: 79.63% / [[251, 110], [79, 488]], 
* Val   accuracy / confusion: 73.73% / [[138, 92], [63, 297]]

------------------------------ Epoch 258 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.382473
- Iter 028 / 029, Loss: 0.370444

* Train accuracy / confusion: 79.96% / [[253, 111], [75, 489]], 
* Val   accuracy / confusion: 70.85% / [[140, 90], [82, 278]]

------------------------------ Epoch 259 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.413895
- Iter 028 / 029, Loss: 0.365216

* Train accuracy / confusion: 80.93% / [[256, 106], [71, 495]], 
* Val   accuracy / confusion: 73.05% / [[145, 85], [74, 286]]

------------------------------ Epoch 260 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.408899
- Iter 028 / 029, Loss: 0.372434

* Train accuracy / confusion: 79.20% / [[251, 110], [83, 484]], 
* Val   accuracy / confusion: 72.20% / [[130, 100], [64, 296]]

------------------------------ Epoch 261 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.431988
- Iter 028 / 029, Loss: 0.372124

* Train accuracy / confusion: 80.50% / [[254, 107], [74, 493]], 
* Val   accuracy / confusion: 73.05% / [[140, 90], [69, 291]]

------------------------------ Epoch 262 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.458662
- Iter 028 / 029, Loss: 0.612629

* Train accuracy / confusion: 82.65% / [[266, 96], [65, 501]], 
* Val   accuracy / confusion: 74.41% / [[141, 89], [62, 298]]

------------------------------ Epoch 263 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.387324
- Iter 028 / 029, Loss: 0.338522

* Train accuracy / confusion: 80.93% / [[257, 103], [74, 494]], 
* Val   accuracy / confusion: 74.41% / [[143, 87], [64, 296]]

------------------------------ Epoch 264 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.426846
- Iter 028 / 029, Loss: 0.482811

* Train accuracy / confusion: 81.25% / [[253, 105], [69, 501]], 
* Val   accuracy / confusion: 72.03% / [[141, 89], [76, 284]]

------------------------------ Epoch 265 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.440405
- Iter 028 / 029, Loss: 0.274789

* Train accuracy / confusion: 81.79% / [[262, 99], [70, 497]], 
* Val   accuracy / confusion: 74.07% / [[135, 95], [58, 302]]

------------------------------ Epoch 266 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.321360
- Iter 028 / 029, Loss: 0.369722

* Train accuracy / confusion: 81.47% / [[256, 105], [67, 500]], 
* Val   accuracy / confusion: 73.39% / [[135, 95], [62, 298]]

------------------------------ Epoch 267 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.334689
- Iter 028 / 029, Loss: 0.440808

* Train accuracy / confusion: 80.93% / [[262, 100], [77, 489]], 
* Val   accuracy / confusion: 73.90% / [[148, 82], [72, 288]]

------------------------------ Epoch 268 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.570910
- Iter 028 / 029, Loss: 0.474815

* Train accuracy / confusion: 79.74% / [[254, 102], [86, 486]], 
* Val   accuracy / confusion: 73.05% / [[145, 85], [74, 286]]

------------------------------ Epoch 269 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.545338
- Iter 028 / 029, Loss: 0.587368

* Train accuracy / confusion: 80.50% / [[257, 101], [80, 490]], 
* Val   accuracy / confusion: 73.22% / [[144, 86], [72, 288]]

------------------------------ Epoch 270 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.359212
- Iter 028 / 029, Loss: 0.448548

* Train accuracy / confusion: 81.90% / [[266, 96], [72, 494]], 
* Val   accuracy / confusion: 73.22% / [[132, 98], [60, 300]]

------------------------------ Epoch 271 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.616089
- Iter 028 / 029, Loss: 0.427669

* Train accuracy / confusion: 81.79% / [[262, 99], [70, 497]], 
* Val   accuracy / confusion: 71.86% / [[137, 93], [73, 287]]

------------------------------ Epoch 272 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.309798
- Iter 028 / 029, Loss: 0.376248

* Train accuracy / confusion: 80.28% / [[263, 102], [81, 482]], 
* Val   accuracy / confusion: 72.54% / [[141, 89], [73, 287]]

------------------------------ Epoch 273 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.284430
- Iter 028 / 029, Loss: 0.475884

* Train accuracy / confusion: 80.82% / [[260, 101], [77, 490]], 
* Val   accuracy / confusion: 74.07% / [[149, 81], [72, 288]]

------------------------------ Epoch 274 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.637052
- Iter 028 / 029, Loss: 0.400380

* Train accuracy / confusion: 80.71% / [[252, 107], [72, 497]], 
* Val   accuracy / confusion: 72.20% / [[143, 87], [77, 283]]

------------------------------ Epoch 275 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.445379
- Iter 028 / 029, Loss: 0.690304

* Train accuracy / confusion: 79.53% / [[253, 110], [80, 485]], 
* Val   accuracy / confusion: 73.22% / [[144, 86], [72, 288]]

------------------------------ Epoch 276 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.614318
- Iter 028 / 029, Loss: 0.427903

* Train accuracy / confusion: 80.60% / [[257, 101], [79, 491]], 
* Val   accuracy / confusion: 72.37% / [[135, 95], [68, 292]]

------------------------------ Epoch 277 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.579139
- Iter 028 / 029, Loss: 0.424818

* Train accuracy / confusion: 80.71% / [[260, 101], [78, 489]], 
* Val   accuracy / confusion: 71.69% / [[134, 96], [71, 289]]

------------------------------ Epoch 278 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.420949
- Iter 028 / 029, Loss: 0.361620

* Train accuracy / confusion: 81.90% / [[268, 87], [81, 492]], 
* Val   accuracy / confusion: 71.02% / [[137, 93], [78, 282]]

------------------------------ Epoch 279 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.260656
- Iter 028 / 029, Loss: 0.416738

* Train accuracy / confusion: 80.50% / [[258, 101], [80, 489]], 
* Val   accuracy / confusion: 72.03% / [[135, 95], [70, 290]]

------------------------------ Epoch 280 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.504265
- Iter 028 / 029, Loss: 0.637332

* Train accuracy / confusion: 81.57% / [[258, 105], [66, 499]], 
* Val   accuracy / confusion: 71.19% / [[138, 92], [78, 282]]

------------------------------ Epoch 281 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.356502
- Iter 028 / 029, Loss: 0.438190

* Train accuracy / confusion: 83.08% / [[269, 93], [64, 502]], 
* Val   accuracy / confusion: 72.71% / [[136, 94], [67, 293]]

------------------------------ Epoch 282 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.373236
- Iter 028 / 029, Loss: 0.366292

* Train accuracy / confusion: 81.79% / [[268, 93], [76, 491]], 
* Val   accuracy / confusion: 72.37% / [[157, 73], [90, 270]]

------------------------------ Epoch 283 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.412539
- Iter 028 / 029, Loss: 0.445665

* Train accuracy / confusion: 80.17% / [[255, 107], [77, 489]], 
* Val   accuracy / confusion: 72.37% / [[135, 95], [68, 292]]

------------------------------ Epoch 284 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.574320
- Iter 028 / 029, Loss: 0.288466

* Train accuracy / confusion: 79.31% / [[254, 109], [83, 482]], 
* Val   accuracy / confusion: 70.00% / [[151, 79], [98, 262]]

------------------------------ Epoch 285 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.487692
- Iter 028 / 029, Loss: 0.336554

* Train accuracy / confusion: 77.91% / [[246, 114], [91, 477]], 
* Val   accuracy / confusion: 73.22% / [[135, 95], [63, 297]]

------------------------------ Epoch 286 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.448271
- Iter 028 / 029, Loss: 0.338136

* Train accuracy / confusion: 81.79% / [[258, 103], [66, 501]], 
* Val   accuracy / confusion: 72.37% / [[131, 99], [64, 296]]

------------------------------ Epoch 287 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.565276
- Iter 028 / 029, Loss: 0.485924

* Train accuracy / confusion: 78.88% / [[252, 113], [83, 480]], 
* Val   accuracy / confusion: 72.88% / [[140, 90], [70, 290]]

------------------------------ Epoch 288 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.460973
- Iter 028 / 029, Loss: 0.378190

* Train accuracy / confusion: 81.90% / [[264, 95], [73, 496]], 
* Val   accuracy / confusion: 74.92% / [[136, 94], [54, 306]]

------------------------------ Epoch 289 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.330646
- Iter 028 / 029, Loss: 0.414268

* Train accuracy / confusion: 80.60% / [[256, 106], [74, 492]], 
* Val   accuracy / confusion: 73.39% / [[135, 95], [62, 298]]

------------------------------ Epoch 290 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.400722
- Iter 028 / 029, Loss: 0.430411

* Train accuracy / confusion: 81.36% / [[261, 101], [72, 494]], 
* Val   accuracy / confusion: 73.39% / [[144, 86], [71, 289]]

------------------------------ Epoch 291 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.427378
- Iter 028 / 029, Loss: 0.312096

* Train accuracy / confusion: 81.03% / [[257, 108], [68, 495]], 
* Val   accuracy / confusion: 71.02% / [[140, 90], [81, 279]]

------------------------------ Epoch 292 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.335644
- Iter 028 / 029, Loss: 0.478543

* Train accuracy / confusion: 80.39% / [[262, 100], [82, 484]], 
* Val   accuracy / confusion: 72.54% / [[142, 88], [74, 286]]

------------------------------ Epoch 293 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.281949
- Iter 028 / 029, Loss: 0.385843

* Train accuracy / confusion: 81.03% / [[264, 103], [73, 488]], 
* Val   accuracy / confusion: 73.05% / [[143, 87], [72, 288]]

------------------------------ Epoch 294 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.447175
- Iter 028 / 029, Loss: 0.456707

* Train accuracy / confusion: 82.87% / [[272, 95], [64, 497]], 
* Val   accuracy / confusion: 73.73% / [[145, 85], [70, 290]]

------------------------------ Epoch 295 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.294075
- Iter 028 / 029, Loss: 0.467073

* Train accuracy / confusion: 81.25% / [[260, 98], [76, 494]], 
* Val   accuracy / confusion: 72.71% / [[134, 96], [65, 295]]

------------------------------ Epoch 296 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.320081
- Iter 028 / 029, Loss: 0.466752

* Train accuracy / confusion: 80.93% / [[261, 100], [77, 490]], 
* Val   accuracy / confusion: 74.41% / [[144, 86], [65, 295]]

------------------------------ Epoch 297 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.345942
- Iter 028 / 029, Loss: 0.446645

* Train accuracy / confusion: 79.53% / [[251, 109], [81, 487]], 
* Val   accuracy / confusion: 73.56% / [[138, 92], [64, 296]]

------------------------------ Epoch 298 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.327232
- Iter 028 / 029, Loss: 0.487020

* Train accuracy / confusion: 81.68% / [[263, 102], [68, 495]], 
* Val   accuracy / confusion: 72.20% / [[130, 100], [64, 296]]

------------------------------ Epoch 299 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.280095
- Iter 028 / 029, Loss: 0.637355

* Train accuracy / confusion: 80.60% / [[259, 103], [77, 489]], 
* Val   accuracy / confusion: 73.39% / [[141, 89], [68, 292]]

------------------------------ Epoch 300 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.430937
- Iter 028 / 029, Loss: 0.428486

* Train accuracy / confusion: 81.25% / [[264, 99], [75, 490]], 
* Val   accuracy / confusion: 71.86% / [[154, 76], [90, 270]]

------------------------------ Epoch 301 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.637306
- Iter 028 / 029, Loss: 0.369103

* Train accuracy / confusion: 82.22% / [[268, 96], [69, 495]], 
* Val   accuracy / confusion: 72.20% / [[124, 106], [58, 302]]

------------------------------ Epoch 302 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.266371
- Iter 028 / 029, Loss: 0.426550

* Train accuracy / confusion: 80.06% / [[253, 108], [77, 490]], 
* Val   accuracy / confusion: 72.20% / [[133, 97], [67, 293]]

------------------------------ Epoch 303 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.454039
- Iter 028 / 029, Loss: 0.296226

* Train accuracy / confusion: 80.39% / [[256, 106], [76, 490]], 
* Val   accuracy / confusion: 71.36% / [[143, 87], [82, 278]]

------------------------------ Epoch 304 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.356179
- Iter 028 / 029, Loss: 0.463378

* Train accuracy / confusion: 82.44% / [[267, 96], [67, 498]], 
* Val   accuracy / confusion: 70.34% / [[115, 115], [60, 300]]

------------------------------ Epoch 305 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.519738
- Iter 028 / 029, Loss: 0.447904

* Train accuracy / confusion: 81.14% / [[261, 104], [71, 492]], 
* Val   accuracy / confusion: 73.90% / [[139, 91], [63, 297]]

------------------------------ Epoch 306 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.577517
- Iter 028 / 029, Loss: 0.302761

* Train accuracy / confusion: 80.71% / [[260, 104], [75, 489]], 
* Val   accuracy / confusion: 72.88% / [[148, 82], [78, 282]]

------------------------------ Epoch 307 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.303099
- Iter 028 / 029, Loss: 0.565464

* Train accuracy / confusion: 82.76% / [[270, 90], [70, 498]], 
* Val   accuracy / confusion: 74.41% / [[145, 85], [66, 294]]

------------------------------ Epoch 308 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.407052
- Iter 028 / 029, Loss: 0.443802

* Train accuracy / confusion: 82.33% / [[264, 96], [68, 500]], 
* Val   accuracy / confusion: 71.36% / [[139, 91], [78, 282]]

------------------------------ Epoch 309 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.332421
- Iter 028 / 029, Loss: 0.525962

* Train accuracy / confusion: 81.25% / [[258, 102], [72, 496]], 
* Val   accuracy / confusion: 73.73% / [[138, 92], [63, 297]]

------------------------------ Epoch 310 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.845273
- Iter 028 / 029, Loss: 0.571436

* Train accuracy / confusion: 79.74% / [[251, 109], [79, 489]], 
* Val   accuracy / confusion: 75.42% / [[157, 73], [72, 288]]

------------------------------ Epoch 311 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.403424
- Iter 028 / 029, Loss: 0.408397

* Train accuracy / confusion: 80.39% / [[262, 102], [80, 484]], 
* Val   accuracy / confusion: 74.07% / [[152, 78], [75, 285]]

------------------------------ Epoch 312 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.464480
- Iter 028 / 029, Loss: 0.577525

* Train accuracy / confusion: 81.47% / [[263, 97], [75, 493]], 
* Val   accuracy / confusion: 72.03% / [[132, 98], [67, 293]]

------------------------------ Epoch 313 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.361056
- Iter 028 / 029, Loss: 0.523566

* Train accuracy / confusion: 81.90% / [[267, 98], [70, 493]], 
* Val   accuracy / confusion: 72.71% / [[134, 96], [65, 295]]

------------------------------ Epoch 314 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.400985
- Iter 028 / 029, Loss: 0.410789

* Train accuracy / confusion: 81.25% / [[264, 102], [72, 490]], 
* Val   accuracy / confusion: 74.58% / [[154, 76], [74, 286]]

------------------------------ Epoch 315 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.467222
- Iter 028 / 029, Loss: 0.565537

* Train accuracy / confusion: 81.25% / [[264, 97], [77, 490]], 
* Val   accuracy / confusion: 72.20% / [[144, 86], [78, 282]]

------------------------------ Epoch 316 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.371523
- Iter 028 / 029, Loss: 0.402516

* Train accuracy / confusion: 82.11% / [[269, 96], [70, 493]], 
* Val   accuracy / confusion: 72.71% / [[128, 102], [59, 301]]

------------------------------ Epoch 317 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.391885
- Iter 028 / 029, Loss: 0.252122

* Train accuracy / confusion: 81.68% / [[270, 95], [75, 488]], 
* Val   accuracy / confusion: 70.85% / [[122, 108], [64, 296]]

------------------------------ Epoch 318 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.388932
- Iter 028 / 029, Loss: 0.273977

* Train accuracy / confusion: 81.14% / [[262, 100], [75, 491]], 
* Val   accuracy / confusion: 74.75% / [[153, 77], [72, 288]]

------------------------------ Epoch 319 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.455936
- Iter 028 / 029, Loss: 0.515860

* Train accuracy / confusion: 80.71% / [[255, 106], [73, 494]], 
* Val   accuracy / confusion: 72.03% / [[130, 100], [65, 295]]

------------------------------ Epoch 320 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.240240
- Iter 028 / 029, Loss: 0.296741

* Train accuracy / confusion: 82.65% / [[267, 96], [65, 500]], 
* Val   accuracy / confusion: 73.73% / [[145, 85], [70, 290]]

------------------------------ Epoch 321 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.437574
- Iter 028 / 029, Loss: 0.266109

* Train accuracy / confusion: 81.14% / [[256, 103], [72, 497]], 
* Val   accuracy / confusion: 74.41% / [[146, 84], [67, 293]]

------------------------------ Epoch 322 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.683775
- Iter 028 / 029, Loss: 0.427831

* Train accuracy / confusion: 79.09% / [[246, 116], [78, 488]], 
* Val   accuracy / confusion: 72.37% / [[143, 87], [76, 284]]

------------------------------ Epoch 323 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.482812
- Iter 028 / 029, Loss: 0.546033

* Train accuracy / confusion: 82.00% / [[263, 100], [67, 498]], 
* Val   accuracy / confusion: 73.90% / [[130, 100], [54, 306]]

------------------------------ Epoch 324 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.501839
- Iter 028 / 029, Loss: 0.460664

* Train accuracy / confusion: 82.76% / [[265, 98], [62, 503]], 
* Val   accuracy / confusion: 73.22% / [[145, 85], [73, 287]]

------------------------------ Epoch 325 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.516066
- Iter 028 / 029, Loss: 0.428397

* Train accuracy / confusion: 82.22% / [[269, 94], [71, 494]], 
* Val   accuracy / confusion: 75.08% / [[146, 84], [63, 297]]

------------------------------ Epoch 326 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.519671
- Iter 028 / 029, Loss: 0.283041

* Train accuracy / confusion: 81.57% / [[253, 103], [68, 504]], 
* Val   accuracy / confusion: 72.20% / [[126, 104], [60, 300]]

------------------------------ Epoch 327 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.349742
- Iter 028 / 029, Loss: 0.500449

* Train accuracy / confusion: 82.11% / [[261, 102], [64, 501]], 
* Val   accuracy / confusion: 73.22% / [[138, 92], [66, 294]]

------------------------------ Epoch 328 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.302171
- Iter 028 / 029, Loss: 0.434067

* Train accuracy / confusion: 81.25% / [[263, 95], [79, 491]], 
* Val   accuracy / confusion: 70.85% / [[148, 82], [90, 270]]

------------------------------ Epoch 329 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.454405
- Iter 028 / 029, Loss: 0.519526

* Train accuracy / confusion: 81.03% / [[259, 100], [76, 493]], 
* Val   accuracy / confusion: 72.71% / [[147, 83], [78, 282]]

------------------------------ Epoch 330 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.427374
- Iter 028 / 029, Loss: 0.359207

* Train accuracy / confusion: 81.25% / [[250, 109], [65, 504]], 
* Val   accuracy / confusion: 73.05% / [[117, 113], [46, 314]]

------------------------------ Epoch 331 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.360373
- Iter 028 / 029, Loss: 0.477678

* Train accuracy / confusion: 82.87% / [[269, 95], [64, 500]], 
* Val   accuracy / confusion: 73.90% / [[145, 85], [69, 291]]

------------------------------ Epoch 332 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.435144
- Iter 028 / 029, Loss: 0.443523

* Train accuracy / confusion: 82.11% / [[255, 101], [65, 507]], 
* Val   accuracy / confusion: 71.86% / [[135, 95], [71, 289]]

------------------------------ Epoch 333 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.344558
- Iter 028 / 029, Loss: 0.467451

* Train accuracy / confusion: 82.11% / [[265, 100], [66, 497]], 
* Val   accuracy / confusion: 69.66% / [[126, 104], [75, 285]]

------------------------------ Epoch 334 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.354117
- Iter 028 / 029, Loss: 0.479572

* Train accuracy / confusion: 80.71% / [[254, 105], [74, 495]], 
* Val   accuracy / confusion: 75.08% / [[142, 88], [59, 301]]

------------------------------ Epoch 335 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.372707
- Iter 028 / 029, Loss: 0.449140

* Train accuracy / confusion: 80.50% / [[261, 99], [82, 486]], 
* Val   accuracy / confusion: 73.73% / [[139, 91], [64, 296]]

------------------------------ Epoch 336 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.318779
- Iter 028 / 029, Loss: 0.403799

* Train accuracy / confusion: 81.79% / [[258, 109], [60, 501]], 
* Val   accuracy / confusion: 71.69% / [[138, 92], [75, 285]]

------------------------------ Epoch 337 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.321273
- Iter 028 / 029, Loss: 0.513840

* Train accuracy / confusion: 79.63% / [[249, 113], [76, 490]], 
* Val   accuracy / confusion: 73.39% / [[135, 95], [62, 298]]

------------------------------ Epoch 338 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.411957
- Iter 028 / 029, Loss: 0.337696

* Train accuracy / confusion: 80.60% / [[251, 111], [69, 497]], 
* Val   accuracy / confusion: 73.05% / [[128, 102], [57, 303]]

------------------------------ Epoch 339 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.362433
- Iter 028 / 029, Loss: 0.280099

* Train accuracy / confusion: 83.73% / [[272, 89], [62, 505]], 
* Val   accuracy / confusion: 73.73% / [[145, 85], [70, 290]]

------------------------------ Epoch 340 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.422103
- Iter 028 / 029, Loss: 0.575858

* Train accuracy / confusion: 81.36% / [[265, 97], [76, 490]], 
* Val   accuracy / confusion: 71.86% / [[130, 100], [66, 294]]

------------------------------ Epoch 341 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.382880
- Iter 028 / 029, Loss: 0.407819

* Train accuracy / confusion: 81.79% / [[257, 105], [64, 502]], 
* Val   accuracy / confusion: 71.02% / [[134, 96], [75, 285]]

------------------------------ Epoch 342 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.358402
- Iter 028 / 029, Loss: 0.416697

* Train accuracy / confusion: 82.00% / [[265, 97], [70, 496]], 
* Val   accuracy / confusion: 75.08% / [[142, 88], [59, 301]]

------------------------------ Epoch 343 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.492997
- Iter 028 / 029, Loss: 0.479158

* Train accuracy / confusion: 81.03% / [[254, 103], [73, 498]], 
* Val   accuracy / confusion: 70.68% / [[138, 92], [81, 279]]

------------------------------ Epoch 344 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.636233
- Iter 028 / 029, Loss: 0.410347

* Train accuracy / confusion: 81.79% / [[259, 101], [68, 500]], 
* Val   accuracy / confusion: 72.37% / [[121, 109], [54, 306]]

------------------------------ Epoch 345 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.544294
- Iter 028 / 029, Loss: 0.487014

* Train accuracy / confusion: 81.57% / [[264, 99], [72, 493]], 
* Val   accuracy / confusion: 72.20% / [[127, 103], [61, 299]]

------------------------------ Epoch 346 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.428352
- Iter 028 / 029, Loss: 0.552984

* Train accuracy / confusion: 80.50% / [[253, 113], [68, 494]], 
* Val   accuracy / confusion: 70.34% / [[138, 92], [83, 277]]

------------------------------ Epoch 347 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.335964
- Iter 028 / 029, Loss: 0.265250

* Train accuracy / confusion: 81.25% / [[256, 107], [67, 498]], 
* Val   accuracy / confusion: 73.56% / [[144, 86], [70, 290]]

------------------------------ Epoch 348 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.434473
- Iter 028 / 029, Loss: 0.435927

* Train accuracy / confusion: 81.36% / [[258, 102], [71, 497]], 
* Val   accuracy / confusion: 73.90% / [[144, 86], [68, 292]]

------------------------------ Epoch 349 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.282493
- Iter 028 / 029, Loss: 0.324278

* Train accuracy / confusion: 81.03% / [[255, 109], [67, 497]], 
* Val   accuracy / confusion: 72.54% / [[125, 105], [57, 303]]

------------------------------ Epoch 350 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.244242
- Iter 028 / 029, Loss: 0.445761

* Train accuracy / confusion: 81.47% / [[259, 103], [69, 497]], 
* Val   accuracy / confusion: 72.71% / [[137, 93], [68, 292]]

------------------------------ Epoch 351 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.269682
- Iter 028 / 029, Loss: 0.379758

* Train accuracy / confusion: 81.57% / [[266, 99], [72, 491]], 
* Val   accuracy / confusion: 73.90% / [[142, 88], [66, 294]]

------------------------------ Epoch 352 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.247774
- Iter 028 / 029, Loss: 0.307892

* Train accuracy / confusion: 81.14% / [[261, 103], [72, 492]], 
* Val   accuracy / confusion: 72.88% / [[142, 88], [72, 288]]

------------------------------ Epoch 353 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.442331
- Iter 028 / 029, Loss: 0.256469

* Train accuracy / confusion: 81.03% / [[261, 101], [75, 491]], 
* Val   accuracy / confusion: 72.20% / [[147, 83], [81, 279]]

------------------------------ Epoch 354 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.556814
- Iter 028 / 029, Loss: 0.277774

* Train accuracy / confusion: 81.90% / [[265, 96], [72, 495]], 
* Val   accuracy / confusion: 72.71% / [[129, 101], [60, 300]]

------------------------------ Epoch 355 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.214637
- Iter 028 / 029, Loss: 0.486333

* Train accuracy / confusion: 82.11% / [[264, 98], [68, 498]], 
* Val   accuracy / confusion: 74.58% / [[151, 79], [71, 289]]

------------------------------ Epoch 356 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.590416
- Iter 028 / 029, Loss: 0.366883

* Train accuracy / confusion: 82.65% / [[261, 97], [64, 506]], 
* Val   accuracy / confusion: 73.56% / [[135, 95], [61, 299]]

------------------------------ Epoch 357 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.395113
- Iter 028 / 029, Loss: 0.309485

* Train accuracy / confusion: 81.68% / [[266, 97], [73, 492]], 
* Val   accuracy / confusion: 73.56% / [[145, 85], [71, 289]]

------------------------------ Epoch 358 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.347010
- Iter 028 / 029, Loss: 0.332888

* Train accuracy / confusion: 82.11% / [[263, 100], [66, 499]], 
* Val   accuracy / confusion: 72.20% / [[126, 104], [60, 300]]

------------------------------ Epoch 359 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.291474
- Iter 028 / 029, Loss: 0.472672

* Train accuracy / confusion: 81.14% / [[261, 105], [70, 492]], 
* Val   accuracy / confusion: 71.69% / [[137, 93], [74, 286]]

------------------------------ Epoch 360 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.314287
- Iter 028 / 029, Loss: 0.397021

* Train accuracy / confusion: 83.08% / [[273, 91], [66, 498]], 
* Val   accuracy / confusion: 72.54% / [[119, 111], [51, 309]]

------------------------------ Epoch 361 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.344737
- Iter 028 / 029, Loss: 0.423284

* Train accuracy / confusion: 80.60% / [[254, 104], [76, 494]], 
* Val   accuracy / confusion: 71.86% / [[141, 89], [77, 283]]

------------------------------ Epoch 362 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.575588
- Iter 028 / 029, Loss: 0.410089

* Train accuracy / confusion: 81.03% / [[259, 103], [73, 493]], 
* Val   accuracy / confusion: 70.68% / [[146, 84], [89, 271]]

------------------------------ Epoch 363 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.565509
- Iter 028 / 029, Loss: 0.422469

* Train accuracy / confusion: 81.03% / [[260, 107], [69, 492]], 
* Val   accuracy / confusion: 74.24% / [[151, 79], [73, 287]]

------------------------------ Epoch 364 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.299474
- Iter 028 / 029, Loss: 0.369447

* Train accuracy / confusion: 80.39% / [[255, 108], [74, 491]], 
* Val   accuracy / confusion: 72.71% / [[128, 102], [59, 301]]

------------------------------ Epoch 365 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.529390
- Iter 028 / 029, Loss: 0.296582

* Train accuracy / confusion: 81.79% / [[267, 96], [73, 492]], 
* Val   accuracy / confusion: 72.88% / [[140, 90], [70, 290]]

------------------------------ Epoch 366 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.239761
- Iter 028 / 029, Loss: 0.351598

* Train accuracy / confusion: 81.03% / [[262, 99], [77, 490]], 
* Val   accuracy / confusion: 73.39% / [[139, 91], [66, 294]]

------------------------------ Epoch 367 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.418054
- Iter 028 / 029, Loss: 0.345788

* Train accuracy / confusion: 81.57% / [[258, 104], [67, 499]], 
* Val   accuracy / confusion: 73.90% / [[142, 88], [66, 294]]

------------------------------ Epoch 368 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.348856
- Iter 028 / 029, Loss: 0.294819

* Train accuracy / confusion: 82.00% / [[257, 103], [64, 504]], 
* Val   accuracy / confusion: 71.86% / [[129, 101], [65, 295]]

------------------------------ Epoch 369 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.329408
- Iter 028 / 029, Loss: 0.400508

* Train accuracy / confusion: 82.11% / [[255, 107], [59, 507]], 
* Val   accuracy / confusion: 73.90% / [[134, 96], [58, 302]]

------------------------------ Epoch 370 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.433856
- Iter 028 / 029, Loss: 0.406458

* Train accuracy / confusion: 82.11% / [[260, 104], [62, 502]], 
* Val   accuracy / confusion: 75.25% / [[137, 93], [53, 307]]

------------------------------ Epoch 371 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.382700
- Iter 028 / 029, Loss: 0.353008

* Train accuracy / confusion: 80.71% / [[254, 107], [72, 495]], 
* Val   accuracy / confusion: 72.37% / [[130, 100], [63, 297]]

------------------------------ Epoch 372 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.498722
- Iter 028 / 029, Loss: 0.484345

* Train accuracy / confusion: 79.74% / [[248, 114], [74, 492]], 
* Val   accuracy / confusion: 74.07% / [[139, 91], [62, 298]]

------------------------------ Epoch 373 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.452542
- Iter 028 / 029, Loss: 0.463277

* Train accuracy / confusion: 83.19% / [[266, 100], [56, 506]], 
* Val   accuracy / confusion: 73.90% / [[150, 80], [74, 286]]

------------------------------ Epoch 374 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.448078
- Iter 028 / 029, Loss: 0.289718

* Train accuracy / confusion: 82.97% / [[274, 91], [67, 496]], 
* Val   accuracy / confusion: 73.05% / [[144, 86], [73, 287]]

------------------------------ Epoch 375 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.260672
- Iter 028 / 029, Loss: 0.350046

* Train accuracy / confusion: 81.57% / [[253, 108], [63, 504]], 
* Val   accuracy / confusion: 72.20% / [[123, 107], [57, 303]]

------------------------------ Epoch 376 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.569342
- Iter 028 / 029, Loss: 0.495123

* Train accuracy / confusion: 79.09% / [[247, 113], [81, 487]], 
* Val   accuracy / confusion: 72.37% / [[126, 104], [59, 301]]

------------------------------ Epoch 377 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.406905
- Iter 028 / 029, Loss: 0.383160

* Train accuracy / confusion: 82.11% / [[264, 98], [68, 498]], 
* Val   accuracy / confusion: 73.22% / [[142, 88], [70, 290]]

------------------------------ Epoch 378 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.302654
- Iter 028 / 029, Loss: 0.422823

* Train accuracy / confusion: 83.73% / [[263, 98], [53, 514]], 
* Val   accuracy / confusion: 73.90% / [[134, 96], [58, 302]]

------------------------------ Epoch 379 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.426390
- Iter 028 / 029, Loss: 0.324113

* Train accuracy / confusion: 81.68% / [[257, 102], [68, 501]], 
* Val   accuracy / confusion: 72.71% / [[131, 99], [62, 298]]

------------------------------ Epoch 380 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.437760
- Iter 028 / 029, Loss: 0.258664

* Train accuracy / confusion: 81.90% / [[256, 106], [62, 504]], 
* Val   accuracy / confusion: 73.22% / [[143, 87], [71, 289]]

------------------------------ Epoch 381 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.439087
- Iter 028 / 029, Loss: 0.423668

* Train accuracy / confusion: 82.97% / [[273, 90], [68, 497]], 
* Val   accuracy / confusion: 74.92% / [[129, 101], [47, 313]]

------------------------------ Epoch 382 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.425236
- Iter 028 / 029, Loss: 0.289222

* Train accuracy / confusion: 82.97% / [[269, 96], [62, 501]], 
* Val   accuracy / confusion: 73.73% / [[129, 101], [54, 306]]

------------------------------ Epoch 383 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.357248
- Iter 028 / 029, Loss: 0.264046

* Train accuracy / confusion: 80.93% / [[260, 106], [71, 491]], 
* Val   accuracy / confusion: 72.37% / [[136, 94], [69, 291]]

------------------------------ Epoch 384 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.377271
- Iter 028 / 029, Loss: 0.482548

* Train accuracy / confusion: 80.82% / [[259, 106], [72, 491]], 
* Val   accuracy / confusion: 76.10% / [[150, 80], [61, 299]]

------------------------------ Epoch 385 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.348376
- Iter 028 / 029, Loss: 0.645275

* Train accuracy / confusion: 81.03% / [[262, 94], [82, 490]], 
* Val   accuracy / confusion: 72.37% / [[141, 89], [74, 286]]

------------------------------ Epoch 386 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.319788
- Iter 028 / 029, Loss: 0.446662

* Train accuracy / confusion: 82.00% / [[266, 94], [73, 495]], 
* Val   accuracy / confusion: 72.54% / [[146, 84], [78, 282]]

------------------------------ Epoch 387 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.426928
- Iter 028 / 029, Loss: 0.407937

* Train accuracy / confusion: 81.68% / [[263, 101], [69, 495]], 
* Val   accuracy / confusion: 72.37% / [[140, 90], [73, 287]]

------------------------------ Epoch 388 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.396897
- Iter 028 / 029, Loss: 0.492409

* Train accuracy / confusion: 82.54% / [[264, 96], [66, 502]], 
* Val   accuracy / confusion: 74.07% / [[134, 96], [57, 303]]

------------------------------ Epoch 389 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.380194
- Iter 028 / 029, Loss: 0.478947

* Train accuracy / confusion: 81.68% / [[262, 102], [68, 496]], 
* Val   accuracy / confusion: 72.20% / [[131, 99], [65, 295]]

------------------------------ Epoch 390 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.259582
- Iter 028 / 029, Loss: 0.434206

* Train accuracy / confusion: 81.68% / [[268, 95], [75, 490]], 
* Val   accuracy / confusion: 72.37% / [[136, 94], [69, 291]]

------------------------------ Epoch 391 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.515442
- Iter 028 / 029, Loss: 0.464316

* Train accuracy / confusion: 82.87% / [[269, 91], [68, 500]], 
* Val   accuracy / confusion: 73.90% / [[140, 90], [64, 296]]

------------------------------ Epoch 392 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.387395
- Iter 028 / 029, Loss: 0.498621

* Train accuracy / confusion: 82.00% / [[272, 92], [75, 489]], 
* Val   accuracy / confusion: 72.88% / [[136, 94], [66, 294]]

------------------------------ Epoch 393 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.382962
- Iter 028 / 029, Loss: 0.338390

* Train accuracy / confusion: 82.97% / [[265, 96], [62, 505]], 
* Val   accuracy / confusion: 75.25% / [[157, 73], [73, 287]]

------------------------------ Epoch 394 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.296068
- Iter 028 / 029, Loss: 0.363602

* Train accuracy / confusion: 81.47% / [[257, 106], [66, 499]], 
* Val   accuracy / confusion: 74.07% / [[144, 86], [67, 293]]

------------------------------ Epoch 395 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.371624
- Iter 028 / 029, Loss: 0.591197

* Train accuracy / confusion: 81.25% / [[257, 104], [70, 497]], 
* Val   accuracy / confusion: 73.39% / [[139, 91], [66, 294]]

------------------------------ Epoch 396 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.499198
- Iter 028 / 029, Loss: 0.477228

* Train accuracy / confusion: 80.71% / [[251, 114], [65, 498]], 
* Val   accuracy / confusion: 71.86% / [[138, 92], [74, 286]]

------------------------------ Epoch 397 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.295174
- Iter 028 / 029, Loss: 0.518862

* Train accuracy / confusion: 80.82% / [[258, 102], [76, 492]], 
* Val   accuracy / confusion: 73.05% / [[145, 85], [74, 286]]

------------------------------ Epoch 398 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.462105
- Iter 028 / 029, Loss: 0.396340

* Train accuracy / confusion: 82.33% / [[270, 92], [72, 494]], 
* Val   accuracy / confusion: 71.69% / [[128, 102], [65, 295]]

------------------------------ Epoch 399 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.418152
- Iter 028 / 029, Loss: 0.440232

* Train accuracy / confusion: 82.33% / [[269, 97], [67, 495]], 
* Val   accuracy / confusion: 72.88% / [[149, 81], [79, 281]]

------------------------------ Epoch 400 / 500, Learning rate: 2.75e-04 ------------------------------
- Iter 014 / 029, Loss: 0.282839
- Iter 028 / 029, Loss: 0.347396

* Train accuracy / confusion: 82.97% / [[274, 89], [69, 496]], 
* Val   accuracy / confusion: 72.88% / [[138, 92], [68, 292]]

------------------------------ Epoch 401 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.345942
- Iter 028 / 029, Loss: 0.535641

* Train accuracy / confusion: 80.39% / [[263, 97], [85, 483]], 
* Val   accuracy / confusion: 72.54% / [[136, 94], [68, 292]]

------------------------------ Epoch 402 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.543060
- Iter 028 / 029, Loss: 0.246822

* Train accuracy / confusion: 80.82% / [[255, 103], [75, 495]], 
* Val   accuracy / confusion: 74.75% / [[149, 81], [68, 292]]

------------------------------ Epoch 403 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.430310
- Iter 028 / 029, Loss: 0.325491

* Train accuracy / confusion: 82.00% / [[266, 96], [71, 495]], 
* Val   accuracy / confusion: 72.20% / [[143, 87], [77, 283]]

------------------------------ Epoch 404 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.293748
- Iter 028 / 029, Loss: 0.384209

* Train accuracy / confusion: 81.25% / [[262, 97], [77, 492]], 
* Val   accuracy / confusion: 73.90% / [[144, 86], [68, 292]]

------------------------------ Epoch 405 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.378335
- Iter 028 / 029, Loss: 0.373132

* Train accuracy / confusion: 81.79% / [[262, 98], [71, 497]], 
* Val   accuracy / confusion: 72.03% / [[140, 90], [75, 285]]

------------------------------ Epoch 406 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.558456
- Iter 028 / 029, Loss: 0.590828

* Train accuracy / confusion: 81.57% / [[265, 97], [74, 492]], 
* Val   accuracy / confusion: 73.73% / [[145, 85], [70, 290]]

------------------------------ Epoch 407 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.293674
- Iter 028 / 029, Loss: 0.348781

* Train accuracy / confusion: 82.33% / [[265, 98], [66, 499]], 
* Val   accuracy / confusion: 72.20% / [[138, 92], [72, 288]]

------------------------------ Epoch 408 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.610203
- Iter 028 / 029, Loss: 0.397057

* Train accuracy / confusion: 82.97% / [[261, 100], [58, 509]], 
* Val   accuracy / confusion: 73.90% / [[140, 90], [64, 296]]

------------------------------ Epoch 409 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.362008
- Iter 028 / 029, Loss: 0.418117

* Train accuracy / confusion: 81.90% / [[261, 102], [66, 499]], 
* Val   accuracy / confusion: 72.03% / [[134, 96], [69, 291]]

------------------------------ Epoch 410 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.411345
- Iter 028 / 029, Loss: 0.648985

* Train accuracy / confusion: 82.54% / [[261, 100], [62, 505]], 
* Val   accuracy / confusion: 73.39% / [[145, 85], [72, 288]]

------------------------------ Epoch 411 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.540097
- Iter 028 / 029, Loss: 0.523966

* Train accuracy / confusion: 81.57% / [[263, 98], [73, 494]], 
* Val   accuracy / confusion: 70.51% / [[143, 87], [87, 273]]

------------------------------ Epoch 412 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.388189
- Iter 028 / 029, Loss: 0.416926

* Train accuracy / confusion: 82.11% / [[263, 100], [66, 499]], 
* Val   accuracy / confusion: 72.54% / [[139, 91], [71, 289]]

------------------------------ Epoch 413 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.369335
- Iter 028 / 029, Loss: 0.303548

* Train accuracy / confusion: 83.19% / [[269, 94], [62, 503]], 
* Val   accuracy / confusion: 75.25% / [[146, 84], [62, 298]]

------------------------------ Epoch 414 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.288236
- Iter 028 / 029, Loss: 0.371806

* Train accuracy / confusion: 81.47% / [[264, 100], [72, 492]], 
* Val   accuracy / confusion: 74.92% / [[144, 86], [62, 298]]

------------------------------ Epoch 415 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.437463
- Iter 028 / 029, Loss: 0.308299

* Train accuracy / confusion: 81.68% / [[267, 93], [77, 491]], 
* Val   accuracy / confusion: 71.36% / [[138, 92], [77, 283]]

------------------------------ Epoch 416 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.470270
- Iter 028 / 029, Loss: 0.384361

* Train accuracy / confusion: 82.65% / [[268, 93], [68, 499]], 
* Val   accuracy / confusion: 73.56% / [[140, 90], [66, 294]]

------------------------------ Epoch 417 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.376243
- Iter 028 / 029, Loss: 0.432118

* Train accuracy / confusion: 82.33% / [[263, 100], [64, 501]], 
* Val   accuracy / confusion: 74.92% / [[152, 78], [70, 290]]

------------------------------ Epoch 418 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.524779
- Iter 028 / 029, Loss: 0.503572

* Train accuracy / confusion: 81.79% / [[273, 92], [77, 486]], 
* Val   accuracy / confusion: 74.92% / [[140, 90], [58, 302]]

------------------------------ Epoch 419 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.326729
- Iter 028 / 029, Loss: 0.319463

* Train accuracy / confusion: 80.39% / [[253, 109], [73, 493]], 
* Val   accuracy / confusion: 72.88% / [[137, 93], [67, 293]]

------------------------------ Epoch 420 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.314350
- Iter 028 / 029, Loss: 0.232259

* Train accuracy / confusion: 81.57% / [[263, 97], [74, 494]], 
* Val   accuracy / confusion: 74.07% / [[146, 84], [69, 291]]

------------------------------ Epoch 421 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.295432
- Iter 028 / 029, Loss: 0.433015

* Train accuracy / confusion: 82.54% / [[264, 98], [64, 502]], 
* Val   accuracy / confusion: 72.54% / [[143, 87], [75, 285]]

------------------------------ Epoch 422 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.405420
- Iter 028 / 029, Loss: 0.302466

* Train accuracy / confusion: 82.00% / [[266, 101], [66, 495]], 
* Val   accuracy / confusion: 72.20% / [[143, 87], [77, 283]]

------------------------------ Epoch 423 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.453487
- Iter 028 / 029, Loss: 0.462958

* Train accuracy / confusion: 82.97% / [[270, 90], [68, 500]], 
* Val   accuracy / confusion: 71.53% / [[141, 89], [79, 281]]

------------------------------ Epoch 424 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.409293
- Iter 028 / 029, Loss: 0.330438

* Train accuracy / confusion: 82.33% / [[267, 99], [65, 497]], 
* Val   accuracy / confusion: 75.59% / [[144, 86], [58, 302]]

------------------------------ Epoch 425 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.344037
- Iter 028 / 029, Loss: 0.406725

* Train accuracy / confusion: 82.65% / [[266, 99], [62, 501]], 
* Val   accuracy / confusion: 74.75% / [[138, 92], [57, 303]]

------------------------------ Epoch 426 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.422073
- Iter 028 / 029, Loss: 0.569520

* Train accuracy / confusion: 83.41% / [[272, 89], [65, 502]], 
* Val   accuracy / confusion: 73.90% / [[147, 83], [71, 289]]

------------------------------ Epoch 427 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.416923
- Iter 028 / 029, Loss: 0.212020

* Train accuracy / confusion: 82.00% / [[266, 90], [77, 495]], 
* Val   accuracy / confusion: 71.69% / [[142, 88], [79, 281]]

------------------------------ Epoch 428 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.371224
- Iter 028 / 029, Loss: 0.303846

* Train accuracy / confusion: 83.08% / [[268, 96], [61, 503]], 
* Val   accuracy / confusion: 74.07% / [[147, 83], [70, 290]]

------------------------------ Epoch 429 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.328609
- Iter 028 / 029, Loss: 0.554522

* Train accuracy / confusion: 80.60% / [[258, 104], [76, 490]], 
* Val   accuracy / confusion: 74.58% / [[141, 89], [61, 299]]

------------------------------ Epoch 430 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.431328
- Iter 028 / 029, Loss: 0.435530

* Train accuracy / confusion: 83.08% / [[265, 96], [61, 506]], 
* Val   accuracy / confusion: 71.36% / [[140, 90], [79, 281]]

------------------------------ Epoch 431 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.452750
- Iter 028 / 029, Loss: 0.335324

* Train accuracy / confusion: 82.33% / [[260, 100], [64, 504]], 
* Val   accuracy / confusion: 71.36% / [[126, 104], [65, 295]]

------------------------------ Epoch 432 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.364207
- Iter 028 / 029, Loss: 0.442222

* Train accuracy / confusion: 82.65% / [[267, 97], [64, 500]], 
* Val   accuracy / confusion: 72.37% / [[137, 93], [70, 290]]

------------------------------ Epoch 433 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.352609
- Iter 028 / 029, Loss: 0.380674

* Train accuracy / confusion: 82.11% / [[263, 100], [66, 499]], 
* Val   accuracy / confusion: 74.24% / [[142, 88], [64, 296]]

------------------------------ Epoch 434 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.567965
- Iter 028 / 029, Loss: 0.346423

* Train accuracy / confusion: 81.03% / [[258, 106], [70, 494]], 
* Val   accuracy / confusion: 73.56% / [[138, 92], [64, 296]]

------------------------------ Epoch 435 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.411434
- Iter 028 / 029, Loss: 0.340151

* Train accuracy / confusion: 82.00% / [[256, 104], [63, 505]], 
* Val   accuracy / confusion: 74.24% / [[148, 82], [70, 290]]

------------------------------ Epoch 436 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.362837
- Iter 028 / 029, Loss: 0.329406

* Train accuracy / confusion: 82.54% / [[264, 98], [64, 502]], 
* Val   accuracy / confusion: 73.22% / [[144, 86], [72, 288]]

------------------------------ Epoch 437 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.354696
- Iter 028 / 029, Loss: 0.413233

* Train accuracy / confusion: 82.22% / [[266, 99], [66, 497]], 
* Val   accuracy / confusion: 73.39% / [[135, 95], [62, 298]]

------------------------------ Epoch 438 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.365816
- Iter 028 / 029, Loss: 0.290742

* Train accuracy / confusion: 82.44% / [[261, 100], [63, 504]], 
* Val   accuracy / confusion: 73.39% / [[144, 86], [71, 289]]

------------------------------ Epoch 439 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.297706
- Iter 028 / 029, Loss: 0.483229

* Train accuracy / confusion: 83.41% / [[265, 96], [58, 509]], 
* Val   accuracy / confusion: 70.68% / [[126, 104], [69, 291]]

------------------------------ Epoch 440 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.272313
- Iter 028 / 029, Loss: 0.487117

* Train accuracy / confusion: 82.87% / [[268, 97], [62, 501]], 
* Val   accuracy / confusion: 71.19% / [[134, 96], [74, 286]]

------------------------------ Epoch 441 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.416476
- Iter 028 / 029, Loss: 0.401602

* Train accuracy / confusion: 82.54% / [[266, 96], [66, 500]], 
* Val   accuracy / confusion: 72.54% / [[133, 97], [65, 295]]

------------------------------ Epoch 442 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.443110
- Iter 028 / 029, Loss: 0.401612

* Train accuracy / confusion: 82.87% / [[263, 99], [60, 506]], 
* Val   accuracy / confusion: 72.54% / [[133, 97], [65, 295]]

------------------------------ Epoch 443 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.382329
- Iter 028 / 029, Loss: 0.236970

* Train accuracy / confusion: 82.00% / [[264, 100], [67, 497]], 
* Val   accuracy / confusion: 71.36% / [[132, 98], [71, 289]]

------------------------------ Epoch 444 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.376342
- Iter 028 / 029, Loss: 0.392211

* Train accuracy / confusion: 82.00% / [[263, 101], [66, 498]], 
* Val   accuracy / confusion: 71.53% / [[141, 89], [79, 281]]

------------------------------ Epoch 445 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.349500
- Iter 028 / 029, Loss: 0.253842

* Train accuracy / confusion: 81.79% / [[259, 103], [66, 500]], 
* Val   accuracy / confusion: 72.54% / [[141, 89], [73, 287]]

------------------------------ Epoch 446 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.251506
- Iter 028 / 029, Loss: 0.321744

* Train accuracy / confusion: 83.73% / [[270, 92], [59, 507]], 
* Val   accuracy / confusion: 73.56% / [[145, 85], [71, 289]]

------------------------------ Epoch 447 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.432763
- Iter 028 / 029, Loss: 0.372333

* Train accuracy / confusion: 82.44% / [[266, 97], [66, 499]], 
* Val   accuracy / confusion: 73.05% / [[139, 91], [68, 292]]

------------------------------ Epoch 448 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.328596
- Iter 028 / 029, Loss: 0.335799

* Train accuracy / confusion: 82.11% / [[267, 96], [70, 495]], 
* Val   accuracy / confusion: 73.39% / [[152, 78], [79, 281]]

------------------------------ Epoch 449 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.257205
- Iter 028 / 029, Loss: 0.487441

* Train accuracy / confusion: 82.22% / [[258, 103], [62, 505]], 
* Val   accuracy / confusion: 73.56% / [[135, 95], [61, 299]]

------------------------------ Epoch 450 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.444047
- Iter 028 / 029, Loss: 0.383278

* Train accuracy / confusion: 81.90% / [[261, 98], [70, 499]], 
* Val   accuracy / confusion: 72.54% / [[140, 90], [72, 288]]

------------------------------ Epoch 451 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.397259
- Iter 028 / 029, Loss: 0.339583

* Train accuracy / confusion: 83.41% / [[268, 91], [63, 506]], 
* Val   accuracy / confusion: 73.90% / [[137, 93], [61, 299]]

------------------------------ Epoch 452 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.555565
- Iter 028 / 029, Loss: 0.442423

* Train accuracy / confusion: 81.47% / [[264, 95], [77, 492]], 
* Val   accuracy / confusion: 72.71% / [[135, 95], [66, 294]]

------------------------------ Epoch 453 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.467307
- Iter 028 / 029, Loss: 0.380258

* Train accuracy / confusion: 79.96% / [[253, 114], [72, 489]], 
* Val   accuracy / confusion: 74.58% / [[137, 93], [57, 303]]

------------------------------ Epoch 454 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.455848
- Iter 028 / 029, Loss: 0.444122

* Train accuracy / confusion: 82.65% / [[273, 93], [68, 494]], 
* Val   accuracy / confusion: 74.07% / [[144, 86], [67, 293]]

------------------------------ Epoch 455 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.434213
- Iter 028 / 029, Loss: 0.252419

* Train accuracy / confusion: 82.65% / [[267, 98], [63, 500]], 
* Val   accuracy / confusion: 75.08% / [[146, 84], [63, 297]]

------------------------------ Epoch 456 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.479068
- Iter 028 / 029, Loss: 0.545041

* Train accuracy / confusion: 83.41% / [[272, 89], [65, 502]], 
* Val   accuracy / confusion: 73.39% / [[147, 83], [74, 286]]

------------------------------ Epoch 457 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.343753
- Iter 028 / 029, Loss: 0.388393

* Train accuracy / confusion: 81.79% / [[263, 99], [70, 496]], 
* Val   accuracy / confusion: 70.85% / [[133, 97], [75, 285]]

------------------------------ Epoch 458 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.312434
- Iter 028 / 029, Loss: 0.481189

* Train accuracy / confusion: 81.03% / [[258, 101], [75, 494]], 
* Val   accuracy / confusion: 73.39% / [[139, 91], [66, 294]]

------------------------------ Epoch 459 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.379725
- Iter 028 / 029, Loss: 0.315577

* Train accuracy / confusion: 81.79% / [[264, 101], [68, 495]], 
* Val   accuracy / confusion: 72.20% / [[132, 98], [66, 294]]

------------------------------ Epoch 460 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.361602
- Iter 028 / 029, Loss: 0.558350

* Train accuracy / confusion: 82.11% / [[266, 97], [69, 496]], 
* Val   accuracy / confusion: 70.51% / [[132, 98], [76, 284]]

------------------------------ Epoch 461 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.414665
- Iter 028 / 029, Loss: 0.409231

* Train accuracy / confusion: 82.97% / [[262, 100], [58, 508]], 
* Val   accuracy / confusion: 72.88% / [[140, 90], [70, 290]]

------------------------------ Epoch 462 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.305465
- Iter 028 / 029, Loss: 0.271523

* Train accuracy / confusion: 81.57% / [[266, 98], [73, 491]], 
* Val   accuracy / confusion: 72.20% / [[127, 103], [61, 299]]

------------------------------ Epoch 463 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.436162
- Iter 028 / 029, Loss: 0.275824

* Train accuracy / confusion: 83.19% / [[267, 92], [64, 505]], 
* Val   accuracy / confusion: 74.07% / [[138, 92], [61, 299]]

------------------------------ Epoch 464 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.495344
- Iter 028 / 029, Loss: 0.326480

* Train accuracy / confusion: 83.51% / [[265, 95], [58, 510]], 
* Val   accuracy / confusion: 70.68% / [[124, 106], [67, 293]]

------------------------------ Epoch 465 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.589354
- Iter 028 / 029, Loss: 0.323719

* Train accuracy / confusion: 81.47% / [[261, 98], [74, 495]], 
* Val   accuracy / confusion: 74.41% / [[155, 75], [76, 284]]

------------------------------ Epoch 466 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.435321
- Iter 028 / 029, Loss: 0.345872

* Train accuracy / confusion: 82.11% / [[264, 101], [65, 498]], 
* Val   accuracy / confusion: 72.37% / [[130, 100], [63, 297]]

------------------------------ Epoch 467 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.556424
- Iter 028 / 029, Loss: 0.563280

* Train accuracy / confusion: 82.33% / [[262, 102], [62, 502]], 
* Val   accuracy / confusion: 73.22% / [[136, 94], [64, 296]]

------------------------------ Epoch 468 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.336377
- Iter 028 / 029, Loss: 0.332509

* Train accuracy / confusion: 82.54% / [[261, 100], [62, 505]], 
* Val   accuracy / confusion: 70.68% / [[130, 100], [73, 287]]

------------------------------ Epoch 469 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.369090
- Iter 028 / 029, Loss: 0.339190

* Train accuracy / confusion: 82.97% / [[272, 91], [67, 498]], 
* Val   accuracy / confusion: 72.71% / [[135, 95], [66, 294]]

------------------------------ Epoch 470 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.501346
- Iter 028 / 029, Loss: 0.454081

* Train accuracy / confusion: 81.68% / [[261, 100], [70, 497]], 
* Val   accuracy / confusion: 70.51% / [[136, 94], [80, 280]]

------------------------------ Epoch 471 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.372219
- Iter 028 / 029, Loss: 0.436720

* Train accuracy / confusion: 82.33% / [[261, 99], [65, 503]], 
* Val   accuracy / confusion: 70.85% / [[140, 90], [82, 278]]

------------------------------ Epoch 472 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.502718
- Iter 028 / 029, Loss: 0.489460

* Train accuracy / confusion: 81.57% / [[263, 101], [70, 494]], 
* Val   accuracy / confusion: 74.24% / [[143, 87], [65, 295]]

------------------------------ Epoch 473 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.318247
- Iter 028 / 029, Loss: 0.412750

* Train accuracy / confusion: 82.76% / [[268, 92], [68, 500]], 
* Val   accuracy / confusion: 73.56% / [[142, 88], [68, 292]]

------------------------------ Epoch 474 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.331596
- Iter 028 / 029, Loss: 0.442325

* Train accuracy / confusion: 81.90% / [[268, 96], [72, 492]], 
* Val   accuracy / confusion: 74.75% / [[144, 86], [63, 297]]

------------------------------ Epoch 475 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.399215
- Iter 028 / 029, Loss: 0.468462

* Train accuracy / confusion: 82.44% / [[264, 96], [67, 501]], 
* Val   accuracy / confusion: 74.07% / [[141, 89], [64, 296]]

------------------------------ Epoch 476 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.320731
- Iter 028 / 029, Loss: 0.488063

* Train accuracy / confusion: 82.11% / [[267, 95], [71, 495]], 
* Val   accuracy / confusion: 72.20% / [[135, 95], [69, 291]]

------------------------------ Epoch 477 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.307512
- Iter 028 / 029, Loss: 0.386056

* Train accuracy / confusion: 81.90% / [[257, 106], [62, 503]], 
* Val   accuracy / confusion: 74.07% / [[139, 91], [62, 298]]

------------------------------ Epoch 478 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.351812
- Iter 028 / 029, Loss: 0.285818

* Train accuracy / confusion: 81.57% / [[256, 106], [65, 501]], 
* Val   accuracy / confusion: 72.54% / [[138, 92], [70, 290]]

------------------------------ Epoch 479 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.493167
- Iter 028 / 029, Loss: 0.634601

* Train accuracy / confusion: 82.76% / [[262, 101], [59, 506]], 
* Val   accuracy / confusion: 72.20% / [[133, 97], [67, 293]]

------------------------------ Epoch 480 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.531314
- Iter 028 / 029, Loss: 0.344306

* Train accuracy / confusion: 83.41% / [[267, 96], [58, 507]], 
* Val   accuracy / confusion: 71.53% / [[140, 90], [78, 282]]

------------------------------ Epoch 481 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.339256
- Iter 028 / 029, Loss: 0.423119

* Train accuracy / confusion: 83.84% / [[267, 94], [56, 511]], 
* Val   accuracy / confusion: 72.03% / [[139, 91], [74, 286]]

------------------------------ Epoch 482 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.405294
- Iter 028 / 029, Loss: 0.428652

* Train accuracy / confusion: 82.65% / [[265, 95], [66, 502]], 
* Val   accuracy / confusion: 73.56% / [[139, 91], [65, 295]]

------------------------------ Epoch 483 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.249633
- Iter 028 / 029, Loss: 0.466315

* Train accuracy / confusion: 84.38% / [[270, 90], [55, 513]], 
* Val   accuracy / confusion: 72.37% / [[137, 93], [70, 290]]

------------------------------ Epoch 484 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.402961
- Iter 028 / 029, Loss: 0.428418

* Train accuracy / confusion: 85.13% / [[277, 84], [54, 513]], 
* Val   accuracy / confusion: 73.73% / [[138, 92], [63, 297]]

------------------------------ Epoch 485 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.406913
- Iter 028 / 029, Loss: 0.328121

* Train accuracy / confusion: 83.94% / [[273, 93], [56, 506]], 
* Val   accuracy / confusion: 71.53% / [[129, 101], [67, 293]]

------------------------------ Epoch 486 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.347313
- Iter 028 / 029, Loss: 0.402374

* Train accuracy / confusion: 82.11% / [[267, 100], [66, 495]], 
* Val   accuracy / confusion: 71.19% / [[137, 93], [77, 283]]

------------------------------ Epoch 487 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.401665
- Iter 028 / 029, Loss: 0.305311

* Train accuracy / confusion: 81.36% / [[256, 103], [70, 499]], 
* Val   accuracy / confusion: 71.53% / [[134, 96], [72, 288]]

------------------------------ Epoch 488 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.370284
- Iter 028 / 029, Loss: 0.303399

* Train accuracy / confusion: 81.47% / [[258, 99], [73, 498]], 
* Val   accuracy / confusion: 71.36% / [[138, 92], [77, 283]]

------------------------------ Epoch 489 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.292115
- Iter 028 / 029, Loss: 0.360909

* Train accuracy / confusion: 82.76% / [[265, 95], [65, 503]], 
* Val   accuracy / confusion: 74.58% / [[138, 92], [58, 302]]

------------------------------ Epoch 490 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.288336
- Iter 028 / 029, Loss: 0.457211

* Train accuracy / confusion: 83.51% / [[276, 82], [71, 499]], 
* Val   accuracy / confusion: 72.88% / [[137, 93], [67, 293]]

------------------------------ Epoch 491 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.321181
- Iter 028 / 029, Loss: 0.622468

* Train accuracy / confusion: 82.22% / [[265, 94], [71, 498]], 
* Val   accuracy / confusion: 73.22% / [[140, 90], [68, 292]]

------------------------------ Epoch 492 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.309405
- Iter 028 / 029, Loss: 0.238427

* Train accuracy / confusion: 84.27% / [[275, 89], [57, 507]], 
* Val   accuracy / confusion: 74.75% / [[150, 80], [69, 291]]

------------------------------ Epoch 493 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.435387
- Iter 028 / 029, Loss: 0.259644

* Train accuracy / confusion: 83.19% / [[266, 96], [60, 506]], 
* Val   accuracy / confusion: 71.86% / [[135, 95], [71, 289]]

------------------------------ Epoch 494 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.365335
- Iter 028 / 029, Loss: 0.266054

* Train accuracy / confusion: 83.19% / [[266, 94], [62, 506]], 
* Val   accuracy / confusion: 71.69% / [[127, 103], [64, 296]]

------------------------------ Epoch 495 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.437100
- Iter 028 / 029, Loss: 0.288437

* Train accuracy / confusion: 83.51% / [[270, 93], [60, 505]], 
* Val   accuracy / confusion: 70.68% / [[127, 103], [70, 290]]

------------------------------ Epoch 496 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.441537
- Iter 028 / 029, Loss: 0.448774

* Train accuracy / confusion: 83.51% / [[267, 95], [58, 508]], 
* Val   accuracy / confusion: 71.69% / [[127, 103], [64, 296]]

------------------------------ Epoch 497 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.433623
- Iter 028 / 029, Loss: 0.216329

* Train accuracy / confusion: 82.44% / [[265, 97], [66, 500]], 
* Val   accuracy / confusion: 73.05% / [[135, 95], [64, 296]]

------------------------------ Epoch 498 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.573803
- Iter 028 / 029, Loss: 0.383795

* Train accuracy / confusion: 83.08% / [[260, 101], [56, 511]], 
* Val   accuracy / confusion: 71.36% / [[118, 112], [57, 303]]

------------------------------ Epoch 499 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.314825
- Iter 028 / 029, Loss: 0.328990

* Train accuracy / confusion: 81.57% / [[258, 102], [69, 499]], 
* Val   accuracy / confusion: 71.69% / [[132, 98], [69, 291]]

------------------------------ Epoch 500 / 500, Learning rate: 2.75e-05 ------------------------------
- Iter 014 / 029, Loss: 0.455984
- Iter 028 / 029, Loss: 0.519702

* Train accuracy / confusion: 82.33% / [[264, 100], [64, 500]], 
* Val   accuracy / confusion: 73.22% / [[137, 93], [65, 295]]

**************************************** Training Ends ****************************************

- Test accuracy (last model): 73.06%
- Confusion matrix (last model):
 [[ 893  517]
 [ 453 1737]]

- Test accuracy (best model): 71.00%
- Confusion matrix (best model):
 [[ 767  643]
 [ 401 1789]]

# checkpoint save path
if save_checkpoint:
    os.makedirs('checkpoint/', exist_ok=True)
    today = datetime.date.today()
    torch.save(best_model_state, f'checkpoint/{today.year % 100}{today.month:02d}{today.day}_{nb_fname}_ResNet_best')
    torch.save(last_model_state, f'checkpoint/{today.year % 100}{today.month:02d}{today.day}_{nb_fname}_ResNet_last')

print('- Debug table:')
pprint.pp(last_test_debug, indent=2, width=100)

- Debug table:
{ '01183': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01303198_020317'},
  '00697': {'GT': 0, 'Acc': '  0.00%', 'Pred': [0, 30], 'edfname': '00983533_290618'},
  '00825': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01129445_130220'},
  '00504': {'GT': 0, 'Acc': '  0.00%', 'Pred': [0, 30], 'edfname': '00813343_041218'},
  '00192': {'GT': 0, 'Acc': '  6.67%', 'Pred': [2, 28], 'edfname': '00608961_131118'},
  '00134': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '00446328_171116'},
  '00741': {'GT': 0, 'Acc': ' 76.67%', 'Pred': [23, 7], 'edfname': '01025734_280715'},
  '00206': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00616193_090218'},
  '01231': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01334787_211117'},
  '00793': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01086373_020615'},
  '01045': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01235281_191015'},
  '00407': {'GT': 1, 'Acc': ' 73.33%', 'Pred': [8, 22], 'edfname': '00740694_110315'},
  '00669': {'GT': 1, 'Acc': '  0.00%', 'Pred': [30, 0], 'edfname': '00957862_230317'},
  '00843': {'GT': 1, 'Acc': '  0.00%', 'Pred': [30, 0], 'edfname': '01135545_230715'},
  '00029': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00164098_180919'},
  '00299': {'GT': 0, 'Acc': '  0.00%', 'Pred': [0, 30], 'edfname': '00671212_160819'},
  '00702': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00985987_180518'},
  '01069': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01243158_301115'},
  '00913': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01151967_160414'},
  '01307': {'GT': 0, 'Acc': '  3.33%', 'Pred': [1, 29], 'edfname': '01376302_060718'},
  '00638': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00941649_111218'},
  '00286': {'GT': 1, 'Acc': ' 13.33%', 'Pred': [26, 4], 'edfname': '00663561_030414'},
  '00954': {'GT': 1, 'Acc': ' 33.33%', 'Pred': [20, 10], 'edfname': '01178797_240914'},
  '00587': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00894185_250817'},
  '00542': {'GT': 1, 'Acc': ' 90.00%', 'Pred': [3, 27], 'edfname': '00852650_170818'},
  '00996': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '01204692_120315'},
  '00403': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00739162_011215'},
  '00408': {'GT': 0, 'Acc': ' 10.00%', 'Pred': [3, 27], 'edfname': '00740750_110315'},
  '00078': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00324958_271118'},
  '00277': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00657017_281218'},
  '00671': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00958455_200917'},
  '01066': {'GT': 0, 'Acc': ' 63.33%', 'Pred': [19, 11], 'edfname': '01242983_071215'},
  '00965': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01186214'},
  '01125': {'GT': 0, 'Acc': ' 93.33%', 'Pred': [28, 2], 'edfname': '01276737_300616'},
  '00227': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00626957_071217'},
  '00531': {'GT': 0, 'Acc': ' 86.67%', 'Pred': [26, 4], 'edfname': '00840844_250119'},
  '00088': {'GT': 1, 'Acc': ' 46.67%', 'Pred': [16, 14], 'edfname': '00344923_021116'},
  '00267': {'GT': 1, 'Acc': ' 86.67%', 'Pred': [4, 26], 'edfname': '00650465_160318'},
  '00069': {'GT': 1, 'Acc': ' 86.67%', 'Pred': [4, 26], 'edfname': '00307906_230617'},
  '00365': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00712852_060418'},
  '00991': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01203444_090819'},
  '00815': {'GT': 0, 'Acc': ' 70.00%', 'Pred': [21, 9], 'edfname': '01125477_030918'},
  '01351': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01409497_111219'},
  '00065': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00293228_070918'},
  '00952': {'GT': 1, 'Acc': ' 66.67%', 'Pred': [10, 20], 'edfname': '01178672_300518'},
  '00124': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '00418981_060116'},
  '00854': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01138301_230114'},
  '00472': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00784418_201016'},
  '01258': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01348039_181017'},
  '01375': {'GT': 1, 'Acc': ' 53.33%', 'Pred': [14, 16], 'edfname': '01429374_230519'},
  '00885': {'GT': 0, 'Acc': ' 23.33%', 'Pred': [7, 23], 'edfname': '01142810_180214'},
  '00917': {'GT': 0, 'Acc': ' 16.67%', 'Pred': [5, 25], 'edfname': '01154159_230414'},
  '00938': {'GT': 0, 'Acc': '  0.00%', 'Pred': [0, 30], 'edfname': '01161826_050916'},
  '00881': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01141790_190214'},
  '00096': {'GT': 0, 'Acc': ' 83.33%', 'Pred': [25, 5], 'edfname': '00369252_131216'},
  '01075': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01250004_260116'},
  '01165': {'GT': 0, 'Acc': ' 53.33%', 'Pred': [16, 14], 'edfname': '01296533_281116'},
  '01067': {'GT': 1, 'Acc': '  0.00%', 'Pred': [30, 0], 'edfname': '01242984_211215'},
  '00828': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01131959_310118'},
  '01337': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01400560_160419'},
  '00383': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00723110_240419'},
  '00900': {'GT': 0, 'Acc': ' 33.33%', 'Pred': [10, 20], 'edfname': '01147100'},
  '01336': {'GT': 1, 'Acc': ' 60.00%', 'Pred': [12, 18], 'edfname': '01398060_050918'},
  '01115': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01271298_270319'},
  '00667': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00956561_241116'},
  '00439': {'GT': 0, 'Acc': ' 76.67%', 'Pred': [23, 7], 'edfname': '00760780_141118'},
  '00369': {'GT': 1, 'Acc': ' 33.33%', 'Pred': [20, 10], 'edfname': '00715828_111016'},
  '00955': {'GT': 1, 'Acc': ' 80.00%', 'Pred': [6, 24], 'edfname': '01178888_161117'},
  '00300': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00671379_290617'},
  '01196': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '01307883_100217'},
  '00923': {'GT': 0, 'Acc': ' 50.00%', 'Pred': [15, 15], 'edfname': '01155730_070514'},
  '00058': {'GT': 0, 'Acc': ' 23.33%', 'Pred': [7, 23], 'edfname': '00285244_020414'},
  '00584': {'GT': 1, 'Acc': ' 30.00%', 'Pred': [21, 9], 'edfname': '00891889_060717'},
  '00749': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01027623_260916'},
  '01334': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '01396872_021018'},
  '00588': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00895530_090616'},
  '00679': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00963069_150618'},
  '00385': {'GT': 0, 'Acc': '  0.00%', 'Pred': [0, 30], 'edfname': '00723232_270318'},
  '00018': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00128526_180817'},
  '01281': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '01358607_280918'},
  '00651': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00951808_251116'},
  '01253': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01344212_240817'},
  '01035': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01231654_260417'},
  '00551': {'GT': 1, 'Acc': ' 73.33%', 'Pred': [8, 22], 'edfname': '00865039_170816'},
  '00870': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01139947_120214'},
  '00578': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '00888613_080618'},
  '00730': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01011922_270815'},
  '00516': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00823206_130514'},
  '01330': {'GT': 0, 'Acc': ' 80.00%', 'Pred': [24, 6], 'edfname': '01392885_240718'},
  '00944': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '01168853_070316'},
  '00125': {'GT': 0, 'Acc': ' 76.67%', 'Pred': [23, 7], 'edfname': '00418981_090316'},
  '00508': {'GT': 0, 'Acc': ' 90.00%', 'Pred': [27, 3], 'edfname': '00817022_010415'},
  '01317': {'GT': 1, 'Acc': ' 73.33%', 'Pred': [8, 22], 'edfname': '01381606_160518'},
  '00608': {'GT': 1, 'Acc': '  3.33%', 'Pred': [29, 1], 'edfname': '00907971_030217'},
  '00471': {'GT': 1, 'Acc': ' 76.67%', 'Pred': [7, 23], 'edfname': '00784417_100315'},
  '00821': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01128393_300715'},
  '00122': {'GT': 0, 'Acc': ' 90.00%', 'Pred': [27, 3], 'edfname': '00416942_190516'},
  '01007': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01211467_070415'},
  '01247': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01339759_310717'},
  '00173': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00601028_290618'},
  '01026': {'GT': 0, 'Acc': ' 93.33%', 'Pred': [28, 2], 'edfname': '01225123_050815'},
  '01018': {'GT': 1, 'Acc': '  0.00%', 'Pred': [30, 0], 'edfname': '01216443_240518'},
  '00418': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '00745209_220916'},
  '01206': {'GT': 1, 'Acc': '  0.00%', 'Pred': [30, 0], 'edfname': '01314786_200317'},
  '01215': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01321744_130417'},
  '01105': {'GT': 0, 'Acc': ' 13.33%', 'Pred': [4, 26], 'edfname': '01266696_110516'},
  '00598': {'GT': 1, 'Acc': ' 70.00%', 'Pred': [9, 21], 'edfname': '00899964_110414'},
  '00851': {'GT': 0, 'Acc': ' 26.67%', 'Pred': [8, 22], 'edfname': '01138297_230114'},
  '01138': {'GT': 0, 'Acc': ' 53.33%', 'Pred': [16, 14], 'edfname': '01281605_070716'},
  '00079': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00325929_170119'},
  '00245': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00637371_050917'},
  '00591': {'GT': 0, 'Acc': ' 70.00%', 'Pred': [21, 9], 'edfname': '00896386_240914'},
  '00329': {'GT': 0, 'Acc': ' 53.33%', 'Pred': [16, 14], 'edfname': '00685248_150414'},
  '00272': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00651389_281016'},
  '00176': {'GT': 0, 'Acc': ' 73.33%', 'Pred': [22, 8], 'edfname': '00602435_270217'},
  '00807': {'GT': 1, 'Acc': ' 23.33%', 'Pred': [23, 7], 'edfname': '01112291_231115'},
  '00271': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00651252_140618'},
  '00712': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00988278_210915'},
  '00974': {'GT': 1, 'Acc': ' 73.33%', 'Pred': [8, 22], 'edfname': '01193508_171214'},
  '01163': {'GT': 1, 'Acc': '  0.00%', 'Pred': [30, 0], 'edfname': '01296342_141116'}}

Small ResNet-like Model

model = ResNet(block=BasicResBlock, conv_layers=[1, 1, 1, 1], n_fc=3, 
               n_input=train_dataset[0]['signal'].shape[0], n_output=2, n_start=64,
               kernel_size=9, use_age=False)
model = model.to(device, dtype=torch.float32)
print(model)
print()

n = count_parameters(model)
print(f'The Number of parameters of the model: {n:,}')

ResNet(
  (input_stage): Sequential(
    (0): Conv1d(20, 64, kernel_size=(27,), stride=(2,), padding=(13,), bias=False)
    (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (2): ReLU()
  )
  (conv_stage1): Sequential(
    (0): BasicResBlock(
      (conv1): Conv1d(64, 64, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
      (bn1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (conv2): Conv1d(64, 64, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
      (bn2): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (relu): ReLU(inplace=True)
    )
    (1): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)
  )
  (conv_stage2): Sequential(
    (0): BasicResBlock(
      (conv1): Conv1d(64, 128, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
      (bn1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (conv2): Conv1d(128, 128, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
      (bn2): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (relu): ReLU(inplace=True)
      (downsample): Sequential(
        (0): Conv1d(64, 128, kernel_size=(1,), stride=(1,), bias=False)
        (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
    )
    (1): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)
  )
  (conv_stage3): Sequential(
    (0): BasicResBlock(
      (conv1): Conv1d(128, 256, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
      (bn1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (conv2): Conv1d(256, 256, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
      (bn2): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (relu): ReLU(inplace=True)
      (downsample): Sequential(
        (0): Conv1d(128, 256, kernel_size=(1,), stride=(1,), bias=False)
        (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
    )
    (1): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)
  )
  (conv_stage4): Sequential(
    (0): BasicResBlock(
      (conv1): Conv1d(256, 512, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
      (bn1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (conv2): Conv1d(512, 512, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
      (bn2): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (relu): ReLU(inplace=True)
      (downsample): Sequential(
        (0): Conv1d(256, 512, kernel_size=(1,), stride=(1,), bias=False)
        (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
    )
    (1): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)
  )
  (final_pool): AdaptiveAvgPool1d(output_size=1)
  (fc_stage): Sequential(
    (0): Sequential(
      (0): Linear(in_features=512, out_features=256, bias=False)
      (1): Dropout(p=0.1, inplace=False)
      (2): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (3): ReLU()
    )
    (1): Sequential(
      (0): Linear(in_features=256, out_features=128, bias=False)
      (1): Dropout(p=0.1, inplace=False)
      (2): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (3): ReLU()
    )
    (2): Sequential(
      (0): Linear(in_features=128, out_features=64, bias=False)
      (1): Dropout(p=0.1, inplace=False)
      (2): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (3): ReLU()
    )
    (3): Linear(in_features=64, out_features=2, bias=True)
  )
)

The Number of parameters of the model: 5,104,002

record = learning_rate_search(model, 
                              min_log_lr=-4.5, 
                              max_log_lr=-1.4, 
                              trials=300, 
                              epochs=1)
draw_learning_rate_record(record)
best_log_lr = record[np.argmax(np.array([v for lr, v in record]))][0]

# best_log_lr = -2.3
print('best_log_lr:', best_log_lr)

best_log_lr: -3.827056599863147

# reduce the learning after [lr_schedule_step] epochs by a factor of 10
n_epoch = 500
lr_schedule_step = 200
log_interval = len(train_loader) // 2

loss_history = []
train_acc_history = []
val_acc_history = []
best_val_acc = 0

model.reset_weights()
optimizer = optim.AdamW(model.parameters(), lr=10 ** best_log_lr, weight_decay=0.0001)
scheduler = optim.lr_scheduler.StepLR(optimizer, step_size=lr_schedule_step, gamma=0.1)

print(f'{"*"*40} Training Starts {"*"*40}')

for epoch in tqdm(range(1, n_epoch + 1)):
    print(f'{"-"*30} Epoch {epoch:03d} / {n_epoch:03d}, Learning rate: {optimizer.param_groups[-1]["lr"]:.2e} {"-"*30}')
    
    # train
    loss, train_accuracy, train_confusion = train_one_epoch(model, optimizer, log_interval)
    loss_history.extend(loss)
    train_acc_history.append(train_accuracy)
    
    # validation
    val_accuracy, val_confusion = check_val_accuracy(model, repeat=5)
    val_acc_history.append(val_accuracy)
    
    if best_val_acc < val_accuracy:
        best_val_acc = val_accuracy
        best_model_state = deepcopy(model.state_dict())
    
    # learning rate schedule
    scheduler.step()
    
    print()
    print(f'* Train accuracy / confusion: {train_accuracy:.2f}% / {train_confusion.tolist()}, ')
    print(f'* Val   accuracy / confusion: {val_accuracy:.2f}% / {val_confusion.tolist()}')
    print()

print(f'{"*"*40} Training Ends {"*"*40}')

# draw the training loss plot
draw_loss_plot(loss_history)
draw_accuracy_history(train_acc_history, val_acc_history)
    
# test the last model
last_model_state = deepcopy(model.state_dict())
last_test_accuracy, last_test_confusion, last_test_debug = check_test_accuracy(model, repeat=30)

print(f'- Test accuracy (last model): {last_test_accuracy:.2f}%')
print('- Confusion matrix (last model):\n', last_test_confusion)
print()

draw_confusion(last_test_confusion)

# test the best model
model.load_state_dict(best_model_state)
best_test_accuracy, best_test_confusion, best_test_debug = check_test_accuracy(model, repeat=30)

print(f'- Test accuracy (best model): {best_test_accuracy:.2f}%')
print('- Confusion matrix (best model):\n', best_test_confusion)
print()

draw_confusion(best_test_confusion)

**************************************** Training Starts ****************************************

------------------------------ Epoch 001 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.698186
- Iter 028 / 029, Loss: 0.687529

* Train accuracy / confusion: 54.20% / [[198, 164], [261, 305]], 
* Val   accuracy / confusion: 53.56% / [[155, 75], [199, 161]]

------------------------------ Epoch 002 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.715212
- Iter 028 / 029, Loss: 0.628814

* Train accuracy / confusion: 60.13% / [[201, 157], [213, 357]], 
* Val   accuracy / confusion: 63.39% / [[85, 145], [71, 289]]

------------------------------ Epoch 003 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.523305
- Iter 028 / 029, Loss: 0.640459

* Train accuracy / confusion: 67.24% / [[198, 164], [140, 426]], 
* Val   accuracy / confusion: 60.68% / [[179, 51], [181, 179]]

------------------------------ Epoch 004 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.618545
- Iter 028 / 029, Loss: 0.659770

* Train accuracy / confusion: 66.38% / [[189, 174], [138, 427]], 
* Val   accuracy / confusion: 58.31% / [[88, 142], [104, 256]]

------------------------------ Epoch 005 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.674361
- Iter 028 / 029, Loss: 0.597958

* Train accuracy / confusion: 65.09% / [[187, 177], [147, 417]], 
* Val   accuracy / confusion: 61.86% / [[57, 173], [52, 308]]

------------------------------ Epoch 006 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.619505
- Iter 028 / 029, Loss: 0.642829

* Train accuracy / confusion: 67.89% / [[186, 177], [121, 444]], 
* Val   accuracy / confusion: 59.32% / [[39, 191], [49, 311]]

------------------------------ Epoch 007 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.529335
- Iter 028 / 029, Loss: 0.519776

* Train accuracy / confusion: 69.07% / [[182, 183], [104, 459]], 
* Val   accuracy / confusion: 64.07% / [[72, 158], [54, 306]]

------------------------------ Epoch 008 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.642090
- Iter 028 / 029, Loss: 0.510653

* Train accuracy / confusion: 69.72% / [[182, 180], [101, 465]], 
* Val   accuracy / confusion: 64.92% / [[151, 79], [128, 232]]

------------------------------ Epoch 009 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.470005
- Iter 028 / 029, Loss: 0.733318

* Train accuracy / confusion: 70.37% / [[195, 167], [108, 458]], 
* Val   accuracy / confusion: 66.44% / [[117, 113], [85, 275]]

------------------------------ Epoch 010 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.599118
- Iter 028 / 029, Loss: 0.618784

* Train accuracy / confusion: 71.44% / [[202, 158], [107, 461]], 
* Val   accuracy / confusion: 62.37% / [[84, 146], [76, 284]]

------------------------------ Epoch 011 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.558975
- Iter 028 / 029, Loss: 0.601361

* Train accuracy / confusion: 69.29% / [[179, 183], [102, 464]], 
* Val   accuracy / confusion: 65.08% / [[57, 173], [33, 327]]

------------------------------ Epoch 012 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.504687
- Iter 028 / 029, Loss: 0.491317

* Train accuracy / confusion: 70.37% / [[189, 168], [107, 464]], 
* Val   accuracy / confusion: 64.07% / [[59, 171], [41, 319]]

------------------------------ Epoch 013 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.500799
- Iter 028 / 029, Loss: 0.554301

* Train accuracy / confusion: 70.80% / [[208, 152], [119, 449]], 
* Val   accuracy / confusion: 65.25% / [[65, 165], [40, 320]]

------------------------------ Epoch 014 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.430042
- Iter 028 / 029, Loss: 0.738192

* Train accuracy / confusion: 73.28% / [[204, 159], [89, 476]], 
* Val   accuracy / confusion: 62.20% / [[80, 150], [73, 287]]

------------------------------ Epoch 015 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.590494
- Iter 028 / 029, Loss: 0.522257

* Train accuracy / confusion: 71.55% / [[202, 160], [104, 462]], 
* Val   accuracy / confusion: 63.90% / [[99, 131], [82, 278]]

------------------------------ Epoch 016 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.512249
- Iter 028 / 029, Loss: 0.577792

* Train accuracy / confusion: 70.91% / [[189, 174], [96, 469]], 
* Val   accuracy / confusion: 65.08% / [[82, 148], [58, 302]]

------------------------------ Epoch 017 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.498022
- Iter 028 / 029, Loss: 0.556439

* Train accuracy / confusion: 73.81% / [[216, 143], [100, 469]], 
* Val   accuracy / confusion: 63.73% / [[182, 48], [166, 194]]

------------------------------ Epoch 018 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.463858
- Iter 028 / 029, Loss: 0.571341

* Train accuracy / confusion: 72.84% / [[208, 155], [97, 468]], 
* Val   accuracy / confusion: 67.46% / [[87, 143], [49, 311]]

------------------------------ Epoch 019 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.643432
- Iter 028 / 029, Loss: 0.581060

* Train accuracy / confusion: 75.11% / [[223, 138], [93, 474]], 
* Val   accuracy / confusion: 65.76% / [[129, 101], [101, 259]]

------------------------------ Epoch 020 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.505615
- Iter 028 / 029, Loss: 0.485989

* Train accuracy / confusion: 73.92% / [[220, 141], [101, 466]], 
* Val   accuracy / confusion: 65.25% / [[156, 74], [131, 229]]

------------------------------ Epoch 021 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.505145
- Iter 028 / 029, Loss: 0.510340

* Train accuracy / confusion: 74.78% / [[231, 128], [106, 463]], 
* Val   accuracy / confusion: 64.58% / [[65, 165], [44, 316]]

------------------------------ Epoch 022 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.610881
- Iter 028 / 029, Loss: 0.580444

* Train accuracy / confusion: 71.88% / [[203, 157], [104, 464]], 
* Val   accuracy / confusion: 67.12% / [[106, 124], [70, 290]]

------------------------------ Epoch 023 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.351076
- Iter 028 / 029, Loss: 0.545875

* Train accuracy / confusion: 75.65% / [[238, 124], [102, 464]], 
* Val   accuracy / confusion: 54.58% / [[210, 20], [248, 112]]

------------------------------ Epoch 024 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.544713
- Iter 028 / 029, Loss: 0.514779

* Train accuracy / confusion: 75.32% / [[230, 131], [98, 469]], 
* Val   accuracy / confusion: 64.58% / [[158, 72], [137, 223]]

------------------------------ Epoch 025 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.507225
- Iter 028 / 029, Loss: 0.551431

* Train accuracy / confusion: 74.68% / [[221, 142], [93, 472]], 
* Val   accuracy / confusion: 66.95% / [[172, 58], [137, 223]]

------------------------------ Epoch 026 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.350024
- Iter 028 / 029, Loss: 0.454487

* Train accuracy / confusion: 76.62% / [[235, 128], [89, 476]], 
* Val   accuracy / confusion: 61.69% / [[172, 58], [168, 192]]

------------------------------ Epoch 027 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.779407
- Iter 028 / 029, Loss: 0.486255

* Train accuracy / confusion: 73.71% / [[226, 135], [109, 458]], 
* Val   accuracy / confusion: 63.90% / [[82, 148], [65, 295]]

------------------------------ Epoch 028 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.459585
- Iter 028 / 029, Loss: 0.557428

* Train accuracy / confusion: 73.92% / [[227, 132], [110, 459]], 
* Val   accuracy / confusion: 67.12% / [[79, 151], [43, 317]]

------------------------------ Epoch 029 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.624794
- Iter 028 / 029, Loss: 0.463639

* Train accuracy / confusion: 75.54% / [[234, 129], [98, 467]], 
* Val   accuracy / confusion: 67.63% / [[166, 64], [127, 233]]

------------------------------ Epoch 030 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.621245
- Iter 028 / 029, Loss: 0.407795

* Train accuracy / confusion: 76.51% / [[229, 132], [86, 481]], 
* Val   accuracy / confusion: 68.64% / [[106, 124], [61, 299]]

------------------------------ Epoch 031 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.633444
- Iter 028 / 029, Loss: 0.524132

* Train accuracy / confusion: 76.29% / [[228, 132], [88, 480]], 
* Val   accuracy / confusion: 64.75% / [[59, 171], [37, 323]]

------------------------------ Epoch 032 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.501906
- Iter 028 / 029, Loss: 0.336359

* Train accuracy / confusion: 78.02% / [[248, 115], [89, 476]], 
* Val   accuracy / confusion: 68.98% / [[94, 136], [47, 313]]

------------------------------ Epoch 033 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.446459
- Iter 028 / 029, Loss: 0.408054

* Train accuracy / confusion: 77.37% / [[251, 110], [100, 467]], 
* Val   accuracy / confusion: 68.81% / [[118, 112], [72, 288]]

------------------------------ Epoch 034 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.683058
- Iter 028 / 029, Loss: 0.661599

* Train accuracy / confusion: 74.68% / [[224, 139], [96, 469]], 
* Val   accuracy / confusion: 67.63% / [[169, 61], [130, 230]]

------------------------------ Epoch 035 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.417362
- Iter 028 / 029, Loss: 0.508198

* Train accuracy / confusion: 77.37% / [[231, 127], [83, 487]], 
* Val   accuracy / confusion: 67.63% / [[170, 60], [131, 229]]

------------------------------ Epoch 036 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.282501
- Iter 028 / 029, Loss: 0.533660

* Train accuracy / confusion: 76.40% / [[225, 135], [84, 484]], 
* Val   accuracy / confusion: 66.61% / [[113, 117], [80, 280]]

------------------------------ Epoch 037 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.607086
- Iter 028 / 029, Loss: 0.602925

* Train accuracy / confusion: 74.46% / [[235, 127], [110, 456]], 
* Val   accuracy / confusion: 63.90% / [[194, 36], [177, 183]]

------------------------------ Epoch 038 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.456161
- Iter 028 / 029, Loss: 0.395122

* Train accuracy / confusion: 76.19% / [[229, 132], [89, 478]], 
* Val   accuracy / confusion: 67.12% / [[184, 46], [148, 212]]

------------------------------ Epoch 039 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.304781
- Iter 028 / 029, Loss: 0.583587

* Train accuracy / confusion: 76.19% / [[236, 128], [93, 471]], 
* Val   accuracy / confusion: 66.61% / [[71, 159], [38, 322]]

------------------------------ Epoch 040 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.367455
- Iter 028 / 029, Loss: 0.493807

* Train accuracy / confusion: 76.72% / [[237, 122], [94, 475]], 
* Val   accuracy / confusion: 68.81% / [[99, 131], [53, 307]]

------------------------------ Epoch 041 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.515872
- Iter 028 / 029, Loss: 0.452325

* Train accuracy / confusion: 78.02% / [[243, 119], [85, 481]], 
* Val   accuracy / confusion: 62.71% / [[206, 24], [196, 164]]

------------------------------ Epoch 042 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.393204
- Iter 028 / 029, Loss: 0.529149

* Train accuracy / confusion: 76.72% / [[231, 128], [88, 481]], 
* Val   accuracy / confusion: 69.32% / [[161, 69], [112, 248]]

------------------------------ Epoch 043 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.405889
- Iter 028 / 029, Loss: 0.521403

* Train accuracy / confusion: 76.40% / [[240, 121], [98, 469]], 
* Val   accuracy / confusion: 67.46% / [[69, 161], [31, 329]]

------------------------------ Epoch 044 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.603530
- Iter 028 / 029, Loss: 0.554418

* Train accuracy / confusion: 77.48% / [[263, 103], [106, 456]], 
* Val   accuracy / confusion: 68.47% / [[181, 49], [137, 223]]

------------------------------ Epoch 045 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.670914
- Iter 028 / 029, Loss: 0.626721

* Train accuracy / confusion: 78.66% / [[252, 111], [87, 478]], 
* Val   accuracy / confusion: 69.49% / [[128, 102], [78, 282]]

------------------------------ Epoch 046 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.633382
- Iter 028 / 029, Loss: 0.537839

* Train accuracy / confusion: 77.05% / [[231, 132], [81, 484]], 
* Val   accuracy / confusion: 66.61% / [[63, 167], [30, 330]]

------------------------------ Epoch 047 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.510166
- Iter 028 / 029, Loss: 0.517480

* Train accuracy / confusion: 79.53% / [[258, 103], [87, 480]], 
* Val   accuracy / confusion: 64.24% / [[153, 77], [134, 226]]

------------------------------ Epoch 048 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.441441
- Iter 028 / 029, Loss: 0.430894

* Train accuracy / confusion: 78.77% / [[253, 111], [86, 478]], 
* Val   accuracy / confusion: 67.80% / [[149, 81], [109, 251]]

------------------------------ Epoch 049 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.515578
- Iter 028 / 029, Loss: 0.351507

* Train accuracy / confusion: 78.34% / [[257, 100], [101, 470]], 
* Val   accuracy / confusion: 62.88% / [[130, 100], [119, 241]]

------------------------------ Epoch 050 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.527958
- Iter 028 / 029, Loss: 0.421661

* Train accuracy / confusion: 77.48% / [[256, 103], [106, 463]], 
* Val   accuracy / confusion: 63.22% / [[27, 203], [14, 346]]

------------------------------ Epoch 051 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.417858
- Iter 028 / 029, Loss: 0.522573

* Train accuracy / confusion: 76.72% / [[239, 122], [94, 473]], 
* Val   accuracy / confusion: 67.80% / [[104, 126], [64, 296]]

------------------------------ Epoch 052 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.482788
- Iter 028 / 029, Loss: 0.515221

* Train accuracy / confusion: 79.74% / [[257, 103], [85, 483]], 
* Val   accuracy / confusion: 64.92% / [[69, 161], [46, 314]]

------------------------------ Epoch 053 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.539064
- Iter 028 / 029, Loss: 0.397071

* Train accuracy / confusion: 79.63% / [[246, 119], [70, 493]], 
* Val   accuracy / confusion: 61.19% / [[4, 226], [3, 357]]

------------------------------ Epoch 054 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.356146
- Iter 028 / 029, Loss: 0.434334

* Train accuracy / confusion: 78.88% / [[255, 108], [88, 477]], 
* Val   accuracy / confusion: 68.81% / [[163, 67], [117, 243]]

------------------------------ Epoch 055 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.529659
- Iter 028 / 029, Loss: 0.306615

* Train accuracy / confusion: 78.12% / [[260, 100], [103, 465]], 
* Val   accuracy / confusion: 67.46% / [[165, 65], [127, 233]]

------------------------------ Epoch 056 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.489620
- Iter 028 / 029, Loss: 0.460753

* Train accuracy / confusion: 79.74% / [[254, 111], [77, 486]], 
* Val   accuracy / confusion: 52.37% / [[208, 22], [259, 101]]

------------------------------ Epoch 057 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.327300
- Iter 028 / 029, Loss: 0.423009

* Train accuracy / confusion: 76.19% / [[241, 123], [98, 466]], 
* Val   accuracy / confusion: 63.22% / [[106, 124], [93, 267]]

------------------------------ Epoch 058 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.521802
- Iter 028 / 029, Loss: 0.277204

* Train accuracy / confusion: 78.23% / [[253, 106], [96, 473]], 
* Val   accuracy / confusion: 67.63% / [[85, 145], [46, 314]]

------------------------------ Epoch 059 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.332961
- Iter 028 / 029, Loss: 0.639409

* Train accuracy / confusion: 77.59% / [[246, 118], [90, 474]], 
* Val   accuracy / confusion: 68.98% / [[122, 108], [75, 285]]

------------------------------ Epoch 060 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.272853
- Iter 028 / 029, Loss: 0.655067

* Train accuracy / confusion: 77.05% / [[240, 121], [92, 475]], 
* Val   accuracy / confusion: 68.14% / [[159, 71], [117, 243]]

------------------------------ Epoch 061 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.400563
- Iter 028 / 029, Loss: 0.442228

* Train accuracy / confusion: 79.09% / [[260, 104], [90, 474]], 
* Val   accuracy / confusion: 66.78% / [[155, 75], [121, 239]]

------------------------------ Epoch 062 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.280038
- Iter 028 / 029, Loss: 0.333527

* Train accuracy / confusion: 78.99% / [[260, 108], [87, 473]], 
* Val   accuracy / confusion: 69.15% / [[172, 58], [124, 236]]

------------------------------ Epoch 063 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.429542
- Iter 028 / 029, Loss: 0.521057

* Train accuracy / confusion: 80.28% / [[260, 104], [79, 485]], 
* Val   accuracy / confusion: 66.27% / [[160, 70], [129, 231]]

------------------------------ Epoch 064 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.414909
- Iter 028 / 029, Loss: 0.295826

* Train accuracy / confusion: 80.50% / [[272, 89], [92, 475]], 
* Val   accuracy / confusion: 69.32% / [[137, 93], [88, 272]]

------------------------------ Epoch 065 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.279060
- Iter 028 / 029, Loss: 0.383013

* Train accuracy / confusion: 79.31% / [[249, 113], [79, 487]], 
* Val   accuracy / confusion: 70.00% / [[159, 71], [106, 254]]

------------------------------ Epoch 066 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.424772
- Iter 028 / 029, Loss: 0.590908

* Train accuracy / confusion: 77.69% / [[253, 110], [97, 468]], 
* Val   accuracy / confusion: 64.24% / [[180, 50], [161, 199]]

------------------------------ Epoch 067 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.416700
- Iter 028 / 029, Loss: 0.610663

* Train accuracy / confusion: 76.83% / [[242, 116], [99, 471]], 
* Val   accuracy / confusion: 68.98% / [[169, 61], [122, 238]]

------------------------------ Epoch 068 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.526414
- Iter 028 / 029, Loss: 0.452343

* Train accuracy / confusion: 76.72% / [[247, 115], [101, 465]], 
* Val   accuracy / confusion: 70.34% / [[130, 100], [75, 285]]

------------------------------ Epoch 069 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.457093
- Iter 028 / 029, Loss: 0.328435

* Train accuracy / confusion: 78.66% / [[257, 107], [91, 473]], 
* Val   accuracy / confusion: 60.85% / [[207, 23], [208, 152]]

------------------------------ Epoch 070 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.546784
- Iter 028 / 029, Loss: 0.491586

* Train accuracy / confusion: 78.34% / [[242, 120], [81, 485]], 
* Val   accuracy / confusion: 67.63% / [[191, 39], [152, 208]]

------------------------------ Epoch 071 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.325255
- Iter 028 / 029, Loss: 0.467731

* Train accuracy / confusion: 79.74% / [[268, 96], [92, 472]], 
* Val   accuracy / confusion: 67.97% / [[163, 67], [122, 238]]

------------------------------ Epoch 072 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.329815
- Iter 028 / 029, Loss: 0.422901

* Train accuracy / confusion: 79.53% / [[260, 105], [85, 478]], 
* Val   accuracy / confusion: 63.56% / [[186, 44], [171, 189]]

------------------------------ Epoch 073 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.420807
- Iter 028 / 029, Loss: 0.468883

* Train accuracy / confusion: 79.20% / [[258, 104], [89, 477]], 
* Val   accuracy / confusion: 66.78% / [[105, 125], [71, 289]]

------------------------------ Epoch 074 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.417800
- Iter 028 / 029, Loss: 0.471641

* Train accuracy / confusion: 79.63% / [[257, 106], [83, 482]], 
* Val   accuracy / confusion: 67.12% / [[134, 96], [98, 262]]

------------------------------ Epoch 075 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.432854
- Iter 028 / 029, Loss: 0.388851

* Train accuracy / confusion: 80.60% / [[256, 104], [76, 492]], 
* Val   accuracy / confusion: 68.81% / [[133, 97], [87, 273]]

------------------------------ Epoch 076 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.453135
- Iter 028 / 029, Loss: 0.385281

* Train accuracy / confusion: 78.45% / [[250, 114], [86, 478]], 
* Val   accuracy / confusion: 71.36% / [[118, 112], [57, 303]]

------------------------------ Epoch 077 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.749250
- Iter 028 / 029, Loss: 0.256430

* Train accuracy / confusion: 81.36% / [[271, 93], [80, 484]], 
* Val   accuracy / confusion: 68.81% / [[168, 62], [122, 238]]

------------------------------ Epoch 078 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.464180
- Iter 028 / 029, Loss: 0.399760

* Train accuracy / confusion: 79.96% / [[266, 93], [93, 476]], 
* Val   accuracy / confusion: 67.80% / [[142, 88], [102, 258]]

------------------------------ Epoch 079 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.324898
- Iter 028 / 029, Loss: 0.292560

* Train accuracy / confusion: 80.39% / [[267, 93], [89, 479]], 
* Val   accuracy / confusion: 68.14% / [[91, 139], [49, 311]]

------------------------------ Epoch 080 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.300359
- Iter 028 / 029, Loss: 0.846496

* Train accuracy / confusion: 81.25% / [[258, 106], [68, 496]], 
* Val   accuracy / confusion: 71.02% / [[154, 76], [95, 265]]

------------------------------ Epoch 081 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.489035
- Iter 028 / 029, Loss: 0.320615

* Train accuracy / confusion: 80.60% / [[261, 104], [76, 487]], 
* Val   accuracy / confusion: 65.93% / [[181, 49], [152, 208]]

------------------------------ Epoch 082 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.355828
- Iter 028 / 029, Loss: 0.384066

* Train accuracy / confusion: 81.47% / [[269, 91], [81, 487]], 
* Val   accuracy / confusion: 67.12% / [[96, 134], [60, 300]]

------------------------------ Epoch 083 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.297942
- Iter 028 / 029, Loss: 0.431498

* Train accuracy / confusion: 80.28% / [[260, 102], [81, 485]], 
* Val   accuracy / confusion: 71.36% / [[147, 83], [86, 274]]

------------------------------ Epoch 084 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.422333
- Iter 028 / 029, Loss: 0.564923

* Train accuracy / confusion: 82.11% / [[272, 91], [75, 490]], 
* Val   accuracy / confusion: 66.10% / [[200, 30], [170, 190]]

------------------------------ Epoch 085 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.433593
- Iter 028 / 029, Loss: 0.375761

* Train accuracy / confusion: 82.11% / [[267, 98], [68, 495]], 
* Val   accuracy / confusion: 68.98% / [[148, 82], [101, 259]]

------------------------------ Epoch 086 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.281467
- Iter 028 / 029, Loss: 0.381033

* Train accuracy / confusion: 81.47% / [[259, 101], [71, 497]], 
* Val   accuracy / confusion: 70.17% / [[125, 105], [71, 289]]

------------------------------ Epoch 087 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.478534
- Iter 028 / 029, Loss: 0.428718

* Train accuracy / confusion: 79.85% / [[265, 99], [88, 476]], 
* Val   accuracy / confusion: 66.61% / [[66, 164], [33, 327]]

------------------------------ Epoch 088 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.417711
- Iter 028 / 029, Loss: 0.524583

* Train accuracy / confusion: 82.00% / [[264, 98], [69, 497]], 
* Val   accuracy / confusion: 67.46% / [[128, 102], [90, 270]]

------------------------------ Epoch 089 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.357795
- Iter 028 / 029, Loss: 0.435429

* Train accuracy / confusion: 79.53% / [[252, 109], [81, 486]], 
* Val   accuracy / confusion: 65.08% / [[37, 193], [13, 347]]

------------------------------ Epoch 090 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.417206
- Iter 028 / 029, Loss: 0.488656

* Train accuracy / confusion: 82.22% / [[267, 96], [69, 496]], 
* Val   accuracy / confusion: 66.44% / [[201, 29], [169, 191]]

------------------------------ Epoch 091 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.405482
- Iter 028 / 029, Loss: 0.602964

* Train accuracy / confusion: 81.14% / [[257, 103], [72, 496]], 
* Val   accuracy / confusion: 69.32% / [[157, 73], [108, 252]]

------------------------------ Epoch 092 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.314209
- Iter 028 / 029, Loss: 0.390733

* Train accuracy / confusion: 83.84% / [[287, 77], [73, 491]], 
* Val   accuracy / confusion: 66.78% / [[125, 105], [91, 269]]

------------------------------ Epoch 093 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.553693
- Iter 028 / 029, Loss: 0.429307

* Train accuracy / confusion: 82.33% / [[260, 100], [64, 504]], 
* Val   accuracy / confusion: 65.76% / [[140, 90], [112, 248]]

------------------------------ Epoch 094 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.351762
- Iter 028 / 029, Loss: 0.483640

* Train accuracy / confusion: 82.87% / [[276, 85], [74, 493]], 
* Val   accuracy / confusion: 67.12% / [[150, 80], [114, 246]]

------------------------------ Epoch 095 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.517834
- Iter 028 / 029, Loss: 0.334245

* Train accuracy / confusion: 80.50% / [[261, 99], [82, 486]], 
* Val   accuracy / confusion: 65.76% / [[65, 165], [37, 323]]

------------------------------ Epoch 096 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.362136
- Iter 028 / 029, Loss: 0.405534

* Train accuracy / confusion: 82.11% / [[265, 97], [69, 497]], 
* Val   accuracy / confusion: 64.58% / [[173, 57], [152, 208]]

------------------------------ Epoch 097 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.337050
- Iter 028 / 029, Loss: 0.345742

* Train accuracy / confusion: 81.57% / [[281, 80], [91, 476]], 
* Val   accuracy / confusion: 63.73% / [[169, 61], [153, 207]]

------------------------------ Epoch 098 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.369631
- Iter 028 / 029, Loss: 0.557646

* Train accuracy / confusion: 81.79% / [[265, 98], [71, 494]], 
* Val   accuracy / confusion: 67.12% / [[86, 144], [50, 310]]

------------------------------ Epoch 099 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.386847
- Iter 028 / 029, Loss: 0.410402

* Train accuracy / confusion: 80.71% / [[276, 89], [90, 473]], 
* Val   accuracy / confusion: 65.08% / [[45, 185], [21, 339]]

------------------------------ Epoch 100 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.497676
- Iter 028 / 029, Loss: 0.376478

* Train accuracy / confusion: 81.03% / [[267, 93], [83, 485]], 
* Val   accuracy / confusion: 61.36% / [[201, 29], [199, 161]]

------------------------------ Epoch 101 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.404787
- Iter 028 / 029, Loss: 0.457976

* Train accuracy / confusion: 83.30% / [[273, 91], [64, 500]], 
* Val   accuracy / confusion: 67.97% / [[196, 34], [155, 205]]

------------------------------ Epoch 102 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.356446
- Iter 028 / 029, Loss: 0.441851

* Train accuracy / confusion: 82.54% / [[278, 86], [76, 488]], 
* Val   accuracy / confusion: 66.78% / [[155, 75], [121, 239]]

------------------------------ Epoch 103 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.331204
- Iter 028 / 029, Loss: 0.274142

* Train accuracy / confusion: 80.71% / [[269, 94], [85, 480]], 
* Val   accuracy / confusion: 70.34% / [[142, 88], [87, 273]]

------------------------------ Epoch 104 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.879600
- Iter 028 / 029, Loss: 0.328139

* Train accuracy / confusion: 81.25% / [[264, 99], [75, 490]], 
* Val   accuracy / confusion: 69.66% / [[156, 74], [105, 255]]

------------------------------ Epoch 105 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.430471
- Iter 028 / 029, Loss: 0.484554

* Train accuracy / confusion: 82.44% / [[263, 96], [67, 502]], 
* Val   accuracy / confusion: 63.39% / [[65, 165], [51, 309]]

------------------------------ Epoch 106 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.288305
- Iter 028 / 029, Loss: 0.641610

* Train accuracy / confusion: 82.11% / [[274, 92], [74, 488]], 
* Val   accuracy / confusion: 66.61% / [[167, 63], [134, 226]]

------------------------------ Epoch 107 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.226612
- Iter 028 / 029, Loss: 0.269778

* Train accuracy / confusion: 82.33% / [[276, 90], [74, 488]], 
* Val   accuracy / confusion: 70.68% / [[146, 84], [89, 271]]

------------------------------ Epoch 108 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.302967
- Iter 028 / 029, Loss: 0.397816

* Train accuracy / confusion: 82.65% / [[281, 82], [79, 486]], 
* Val   accuracy / confusion: 63.90% / [[187, 43], [170, 190]]

------------------------------ Epoch 109 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.240076
- Iter 028 / 029, Loss: 0.377519

* Train accuracy / confusion: 82.11% / [[274, 90], [76, 488]], 
* Val   accuracy / confusion: 70.34% / [[136, 94], [81, 279]]

------------------------------ Epoch 110 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.356031
- Iter 028 / 029, Loss: 0.281982

* Train accuracy / confusion: 84.38% / [[278, 86], [59, 505]], 
* Val   accuracy / confusion: 68.47% / [[193, 37], [149, 211]]

------------------------------ Epoch 111 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.425375
- Iter 028 / 029, Loss: 0.309075

* Train accuracy / confusion: 82.22% / [[269, 91], [74, 494]], 
* Val   accuracy / confusion: 67.97% / [[159, 71], [118, 242]]

------------------------------ Epoch 112 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.339894
- Iter 028 / 029, Loss: 0.305441

* Train accuracy / confusion: 83.08% / [[282, 78], [79, 489]], 
* Val   accuracy / confusion: 66.78% / [[58, 172], [24, 336]]

------------------------------ Epoch 113 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.289771
- Iter 028 / 029, Loss: 0.405865

* Train accuracy / confusion: 83.73% / [[282, 80], [71, 495]], 
* Val   accuracy / confusion: 70.51% / [[108, 122], [52, 308]]

------------------------------ Epoch 114 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.298463
- Iter 028 / 029, Loss: 0.351230

* Train accuracy / confusion: 82.65% / [[275, 84], [77, 492]], 
* Val   accuracy / confusion: 69.83% / [[101, 129], [49, 311]]

------------------------------ Epoch 115 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.472487
- Iter 028 / 029, Loss: 0.272754

* Train accuracy / confusion: 81.68% / [[266, 95], [75, 492]], 
* Val   accuracy / confusion: 65.25% / [[46, 184], [21, 339]]

------------------------------ Epoch 116 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.257556
- Iter 028 / 029, Loss: 0.405379

* Train accuracy / confusion: 82.97% / [[272, 87], [71, 498]], 
* Val   accuracy / confusion: 68.47% / [[161, 69], [117, 243]]

------------------------------ Epoch 117 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.342884
- Iter 028 / 029, Loss: 0.421663

* Train accuracy / confusion: 85.13% / [[285, 75], [63, 505]], 
* Val   accuracy / confusion: 71.69% / [[128, 102], [65, 295]]

------------------------------ Epoch 118 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.272144
- Iter 028 / 029, Loss: 0.443755

* Train accuracy / confusion: 83.94% / [[279, 79], [70, 500]], 
* Val   accuracy / confusion: 68.98% / [[89, 141], [42, 318]]

------------------------------ Epoch 119 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.333219
- Iter 028 / 029, Loss: 0.342753

* Train accuracy / confusion: 83.19% / [[286, 70], [86, 486]], 
* Val   accuracy / confusion: 69.66% / [[141, 89], [90, 270]]

------------------------------ Epoch 120 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.326050
- Iter 028 / 029, Loss: 0.503710

* Train accuracy / confusion: 82.97% / [[272, 93], [65, 498]], 
* Val   accuracy / confusion: 69.66% / [[102, 128], [51, 309]]

------------------------------ Epoch 121 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.282524
- Iter 028 / 029, Loss: 0.466788

* Train accuracy / confusion: 83.30% / [[271, 90], [65, 502]], 
* Val   accuracy / confusion: 70.51% / [[147, 83], [91, 269]]

------------------------------ Epoch 122 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.404907
- Iter 028 / 029, Loss: 0.478892

* Train accuracy / confusion: 82.97% / [[280, 76], [82, 490]], 
* Val   accuracy / confusion: 71.36% / [[154, 76], [93, 267]]

------------------------------ Epoch 123 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.534379
- Iter 028 / 029, Loss: 0.332228

* Train accuracy / confusion: 84.38% / [[293, 67], [78, 490]], 
* Val   accuracy / confusion: 64.41% / [[195, 35], [175, 185]]

------------------------------ Epoch 124 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.451864
- Iter 028 / 029, Loss: 0.287160

* Train accuracy / confusion: 84.91% / [[280, 84], [56, 508]], 
* Val   accuracy / confusion: 65.25% / [[163, 67], [138, 222]]

------------------------------ Epoch 125 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.389161
- Iter 028 / 029, Loss: 0.338519

* Train accuracy / confusion: 83.19% / [[290, 76], [80, 482]], 
* Val   accuracy / confusion: 64.58% / [[189, 41], [168, 192]]

------------------------------ Epoch 126 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.354309
- Iter 028 / 029, Loss: 0.517235

* Train accuracy / confusion: 84.38% / [[285, 75], [70, 498]], 
* Val   accuracy / confusion: 68.64% / [[174, 56], [129, 231]]

------------------------------ Epoch 127 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.422527
- Iter 028 / 029, Loss: 0.333713

* Train accuracy / confusion: 83.41% / [[282, 79], [75, 492]], 
* Val   accuracy / confusion: 69.15% / [[118, 112], [70, 290]]

------------------------------ Epoch 128 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.550026
- Iter 028 / 029, Loss: 0.489340

* Train accuracy / confusion: 85.56% / [[299, 69], [65, 495]], 
* Val   accuracy / confusion: 67.29% / [[176, 54], [139, 221]]

------------------------------ Epoch 129 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.247807
- Iter 028 / 029, Loss: 0.265827

* Train accuracy / confusion: 83.73% / [[270, 91], [60, 507]], 
* Val   accuracy / confusion: 66.10% / [[192, 38], [162, 198]]

------------------------------ Epoch 130 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.329818
- Iter 028 / 029, Loss: 0.318204

* Train accuracy / confusion: 85.88% / [[290, 70], [61, 507]], 
* Val   accuracy / confusion: 64.41% / [[183, 47], [163, 197]]

------------------------------ Epoch 131 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.344036
- Iter 028 / 029, Loss: 0.334493

* Train accuracy / confusion: 83.84% / [[289, 69], [81, 489]], 
* Val   accuracy / confusion: 64.75% / [[161, 69], [139, 221]]

------------------------------ Epoch 132 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.456120
- Iter 028 / 029, Loss: 0.416587

* Train accuracy / confusion: 84.59% / [[285, 79], [64, 500]], 
* Val   accuracy / confusion: 70.34% / [[154, 76], [99, 261]]

------------------------------ Epoch 133 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.319144
- Iter 028 / 029, Loss: 0.353843

* Train accuracy / confusion: 84.38% / [[284, 75], [70, 499]], 
* Val   accuracy / confusion: 68.14% / [[121, 109], [79, 281]]

------------------------------ Epoch 134 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.381113
- Iter 028 / 029, Loss: 0.359172

* Train accuracy / confusion: 83.84% / [[289, 72], [78, 489]], 
* Val   accuracy / confusion: 69.32% / [[146, 84], [97, 263]]

------------------------------ Epoch 135 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.395957
- Iter 028 / 029, Loss: 0.577980

* Train accuracy / confusion: 84.81% / [[282, 79], [62, 505]], 
* Val   accuracy / confusion: 67.97% / [[184, 46], [143, 217]]

------------------------------ Epoch 136 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.273281
- Iter 028 / 029, Loss: 0.238936

* Train accuracy / confusion: 85.34% / [[290, 73], [63, 502]], 
* Val   accuracy / confusion: 67.46% / [[169, 61], [131, 229]]

------------------------------ Epoch 137 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.547633
- Iter 028 / 029, Loss: 0.298220

* Train accuracy / confusion: 84.38% / [[287, 76], [69, 496]], 
* Val   accuracy / confusion: 66.44% / [[79, 151], [47, 313]]

------------------------------ Epoch 138 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.189201
- Iter 028 / 029, Loss: 0.504941

* Train accuracy / confusion: 85.78% / [[292, 74], [58, 504]], 
* Val   accuracy / confusion: 67.63% / [[144, 86], [105, 255]]

------------------------------ Epoch 139 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.399512
- Iter 028 / 029, Loss: 0.504220

* Train accuracy / confusion: 84.70% / [[296, 66], [76, 490]], 
* Val   accuracy / confusion: 58.47% / [[203, 27], [218, 142]]

------------------------------ Epoch 140 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.321730
- Iter 028 / 029, Loss: 0.420756

* Train accuracy / confusion: 84.48% / [[292, 74], [70, 492]], 
* Val   accuracy / confusion: 69.66% / [[153, 77], [102, 258]]

------------------------------ Epoch 141 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.278959
- Iter 028 / 029, Loss: 0.269391

* Train accuracy / confusion: 85.78% / [[293, 70], [62, 503]], 
* Val   accuracy / confusion: 72.88% / [[132, 98], [62, 298]]

------------------------------ Epoch 142 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.422691
- Iter 028 / 029, Loss: 0.381092

* Train accuracy / confusion: 84.59% / [[297, 71], [72, 488]], 
* Val   accuracy / confusion: 66.61% / [[100, 130], [67, 293]]

------------------------------ Epoch 143 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.214041
- Iter 028 / 029, Loss: 0.335773

* Train accuracy / confusion: 86.64% / [[300, 62], [62, 504]], 
* Val   accuracy / confusion: 67.29% / [[149, 81], [112, 248]]

------------------------------ Epoch 144 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.248449
- Iter 028 / 029, Loss: 0.299402

* Train accuracy / confusion: 88.04% / [[301, 58], [53, 516]], 
* Val   accuracy / confusion: 67.46% / [[149, 81], [111, 249]]

------------------------------ Epoch 145 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.195656
- Iter 028 / 029, Loss: 0.202589

* Train accuracy / confusion: 86.21% / [[293, 71], [57, 507]], 
* Val   accuracy / confusion: 64.58% / [[101, 129], [80, 280]]

------------------------------ Epoch 146 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.413664
- Iter 028 / 029, Loss: 0.344944

* Train accuracy / confusion: 85.24% / [[289, 76], [61, 502]], 
* Val   accuracy / confusion: 67.12% / [[89, 141], [53, 307]]

------------------------------ Epoch 147 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.288344
- Iter 028 / 029, Loss: 0.320950

* Train accuracy / confusion: 85.24% / [[306, 59], [78, 485]], 
* Val   accuracy / confusion: 64.92% / [[183, 47], [160, 200]]

------------------------------ Epoch 148 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.275301
- Iter 028 / 029, Loss: 0.291671

* Train accuracy / confusion: 86.21% / [[299, 66], [62, 501]], 
* Val   accuracy / confusion: 63.39% / [[172, 58], [158, 202]]

------------------------------ Epoch 149 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.466664
- Iter 028 / 029, Loss: 0.302280

* Train accuracy / confusion: 86.42% / [[297, 65], [61, 505]], 
* Val   accuracy / confusion: 68.31% / [[184, 46], [141, 219]]

------------------------------ Epoch 150 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.226072
- Iter 028 / 029, Loss: 0.216319

* Train accuracy / confusion: 87.39% / [[310, 49], [68, 501]], 
* Val   accuracy / confusion: 66.61% / [[79, 151], [46, 314]]

------------------------------ Epoch 151 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.699895
- Iter 028 / 029, Loss: 0.199211

* Train accuracy / confusion: 86.42% / [[288, 71], [55, 514]], 
* Val   accuracy / confusion: 67.46% / [[87, 143], [49, 311]]

------------------------------ Epoch 152 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.295981
- Iter 028 / 029, Loss: 0.258515

* Train accuracy / confusion: 86.85% / [[301, 60], [62, 505]], 
* Val   accuracy / confusion: 66.61% / [[59, 171], [26, 334]]

------------------------------ Epoch 153 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.238793
- Iter 028 / 029, Loss: 0.344754

* Train accuracy / confusion: 85.67% / [[293, 71], [62, 502]], 
* Val   accuracy / confusion: 66.44% / [[116, 114], [84, 276]]

------------------------------ Epoch 154 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.158690
- Iter 028 / 029, Loss: 0.376459

* Train accuracy / confusion: 85.67% / [[291, 67], [66, 504]], 
* Val   accuracy / confusion: 65.25% / [[186, 44], [161, 199]]

------------------------------ Epoch 155 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.384114
- Iter 028 / 029, Loss: 0.302094

* Train accuracy / confusion: 86.53% / [[294, 65], [60, 509]], 
* Val   accuracy / confusion: 66.95% / [[126, 104], [91, 269]]

------------------------------ Epoch 156 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.291608
- Iter 028 / 029, Loss: 0.261074

* Train accuracy / confusion: 87.28% / [[291, 68], [50, 519]], 
* Val   accuracy / confusion: 66.61% / [[111, 119], [78, 282]]

------------------------------ Epoch 157 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.464103
- Iter 028 / 029, Loss: 0.277254

* Train accuracy / confusion: 87.50% / [[310, 51], [65, 502]], 
* Val   accuracy / confusion: 63.90% / [[62, 168], [45, 315]]

------------------------------ Epoch 158 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.249488
- Iter 028 / 029, Loss: 0.226457

* Train accuracy / confusion: 85.78% / [[303, 56], [76, 493]], 
* Val   accuracy / confusion: 64.41% / [[68, 162], [48, 312]]

------------------------------ Epoch 159 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.208204
- Iter 028 / 029, Loss: 0.209639

* Train accuracy / confusion: 86.85% / [[298, 63], [59, 508]], 
* Val   accuracy / confusion: 69.49% / [[119, 111], [69, 291]]

------------------------------ Epoch 160 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.198411
- Iter 028 / 029, Loss: 0.346820

* Train accuracy / confusion: 86.75% / [[297, 63], [60, 508]], 
* Val   accuracy / confusion: 61.69% / [[210, 20], [206, 154]]

------------------------------ Epoch 161 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.333941
- Iter 028 / 029, Loss: 0.255824

* Train accuracy / confusion: 87.50% / [[306, 56], [60, 506]], 
* Val   accuracy / confusion: 65.25% / [[158, 72], [133, 227]]

------------------------------ Epoch 162 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.256804
- Iter 028 / 029, Loss: 0.372789

* Train accuracy / confusion: 87.61% / [[314, 46], [69, 499]], 
* Val   accuracy / confusion: 67.97% / [[135, 95], [94, 266]]

------------------------------ Epoch 163 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.386975
- Iter 028 / 029, Loss: 0.336763

* Train accuracy / confusion: 87.50% / [[309, 56], [60, 503]], 
* Val   accuracy / confusion: 64.58% / [[112, 118], [91, 269]]

------------------------------ Epoch 164 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.212633
- Iter 028 / 029, Loss: 0.342612

* Train accuracy / confusion: 87.72% / [[307, 59], [55, 507]], 
* Val   accuracy / confusion: 69.49% / [[173, 57], [123, 237]]

------------------------------ Epoch 165 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.233889
- Iter 028 / 029, Loss: 0.269753

* Train accuracy / confusion: 87.18% / [[308, 56], [63, 501]], 
* Val   accuracy / confusion: 68.14% / [[152, 78], [110, 250]]

------------------------------ Epoch 166 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.344047
- Iter 028 / 029, Loss: 0.296857

* Train accuracy / confusion: 87.50% / [[306, 53], [63, 506]], 
* Val   accuracy / confusion: 66.78% / [[179, 51], [145, 215]]

------------------------------ Epoch 167 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.308858
- Iter 028 / 029, Loss: 0.462263

* Train accuracy / confusion: 87.93% / [[303, 57], [55, 513]], 
* Val   accuracy / confusion: 70.17% / [[142, 88], [88, 272]]

------------------------------ Epoch 168 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.250379
- Iter 028 / 029, Loss: 0.279839

* Train accuracy / confusion: 88.15% / [[305, 54], [56, 513]], 
* Val   accuracy / confusion: 68.47% / [[152, 78], [108, 252]]

------------------------------ Epoch 169 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.223579
- Iter 028 / 029, Loss: 0.301549

* Train accuracy / confusion: 89.22% / [[305, 54], [46, 523]], 
* Val   accuracy / confusion: 64.75% / [[41, 189], [19, 341]]

------------------------------ Epoch 170 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.298039
- Iter 028 / 029, Loss: 0.455180

* Train accuracy / confusion: 87.61% / [[315, 45], [70, 498]], 
* Val   accuracy / confusion: 63.73% / [[114, 116], [98, 262]]

------------------------------ Epoch 171 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.236673
- Iter 028 / 029, Loss: 0.150578

* Train accuracy / confusion: 90.84% / [[311, 50], [35, 532]], 
* Val   accuracy / confusion: 68.64% / [[87, 143], [42, 318]]

------------------------------ Epoch 172 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.290936
- Iter 028 / 029, Loss: 0.567865

* Train accuracy / confusion: 86.31% / [[295, 65], [62, 506]], 
* Val   accuracy / confusion: 67.12% / [[133, 97], [97, 263]]

------------------------------ Epoch 173 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.305743
- Iter 028 / 029, Loss: 0.270098

* Train accuracy / confusion: 88.69% / [[309, 51], [54, 514]], 
* Val   accuracy / confusion: 67.63% / [[161, 69], [122, 238]]

------------------------------ Epoch 174 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.298845
- Iter 028 / 029, Loss: 0.190199

* Train accuracy / confusion: 88.47% / [[308, 57], [50, 513]], 
* Val   accuracy / confusion: 65.76% / [[126, 104], [98, 262]]

------------------------------ Epoch 175 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.251994
- Iter 028 / 029, Loss: 0.167260

* Train accuracy / confusion: 87.39% / [[307, 59], [58, 504]], 
* Val   accuracy / confusion: 68.14% / [[196, 34], [154, 206]]

------------------------------ Epoch 176 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.249497
- Iter 028 / 029, Loss: 0.271924

* Train accuracy / confusion: 88.69% / [[306, 58], [47, 517]], 
* Val   accuracy / confusion: 67.63% / [[161, 69], [122, 238]]

------------------------------ Epoch 177 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.398975
- Iter 028 / 029, Loss: 0.507382

* Train accuracy / confusion: 86.53% / [[308, 52], [73, 495]], 
* Val   accuracy / confusion: 66.10% / [[126, 104], [96, 264]]

------------------------------ Epoch 178 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.209534
- Iter 028 / 029, Loss: 0.107570

* Train accuracy / confusion: 89.12% / [[304, 57], [44, 523]], 
* Val   accuracy / confusion: 67.29% / [[138, 92], [101, 259]]

------------------------------ Epoch 179 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.316584
- Iter 028 / 029, Loss: 0.315712

* Train accuracy / confusion: 88.47% / [[320, 44], [63, 501]], 
* Val   accuracy / confusion: 72.71% / [[141, 89], [72, 288]]

------------------------------ Epoch 180 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.251558
- Iter 028 / 029, Loss: 0.159415

* Train accuracy / confusion: 87.39% / [[303, 56], [61, 508]], 
* Val   accuracy / confusion: 69.66% / [[143, 87], [92, 268]]

------------------------------ Epoch 181 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.148833
- Iter 028 / 029, Loss: 0.353846

* Train accuracy / confusion: 90.62% / [[311, 52], [35, 530]], 
* Val   accuracy / confusion: 67.63% / [[136, 94], [97, 263]]

------------------------------ Epoch 182 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.244768
- Iter 028 / 029, Loss: 0.407765

* Train accuracy / confusion: 86.42% / [[295, 69], [57, 507]], 
* Val   accuracy / confusion: 64.41% / [[78, 152], [58, 302]]

------------------------------ Epoch 183 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.557929
- Iter 028 / 029, Loss: 0.500565

* Train accuracy / confusion: 89.76% / [[318, 44], [51, 515]], 
* Val   accuracy / confusion: 70.17% / [[175, 55], [121, 239]]

------------------------------ Epoch 184 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.462278
- Iter 028 / 029, Loss: 0.335811

* Train accuracy / confusion: 89.76% / [[304, 57], [38, 529]], 
* Val   accuracy / confusion: 66.10% / [[98, 132], [68, 292]]

------------------------------ Epoch 185 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.191668
- Iter 028 / 029, Loss: 0.339806

* Train accuracy / confusion: 89.66% / [[312, 55], [41, 520]], 
* Val   accuracy / confusion: 70.17% / [[111, 119], [57, 303]]

------------------------------ Epoch 186 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.346722
- Iter 028 / 029, Loss: 0.157116

* Train accuracy / confusion: 89.22% / [[318, 44], [56, 510]], 
* Val   accuracy / confusion: 67.97% / [[116, 114], [75, 285]]

------------------------------ Epoch 187 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.134918
- Iter 028 / 029, Loss: 0.173082

* Train accuracy / confusion: 89.66% / [[312, 47], [49, 520]], 
* Val   accuracy / confusion: 67.80% / [[77, 153], [37, 323]]

------------------------------ Epoch 188 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.352494
- Iter 028 / 029, Loss: 0.207912

* Train accuracy / confusion: 89.44% / [[311, 51], [47, 519]], 
* Val   accuracy / confusion: 62.71% / [[35, 195], [25, 335]]

------------------------------ Epoch 189 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.189298
- Iter 028 / 029, Loss: 0.260793

* Train accuracy / confusion: 89.76% / [[312, 47], [48, 521]], 
* Val   accuracy / confusion: 66.95% / [[70, 160], [35, 325]]

------------------------------ Epoch 190 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.344591
- Iter 028 / 029, Loss: 0.390861

* Train accuracy / confusion: 87.28% / [[302, 60], [58, 508]], 
* Val   accuracy / confusion: 67.63% / [[166, 64], [127, 233]]

------------------------------ Epoch 191 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.230010
- Iter 028 / 029, Loss: 0.352146

* Train accuracy / confusion: 90.19% / [[323, 39], [52, 514]], 
* Val   accuracy / confusion: 68.81% / [[138, 92], [92, 268]]

------------------------------ Epoch 192 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.330768
- Iter 028 / 029, Loss: 0.151059

* Train accuracy / confusion: 89.44% / [[301, 60], [38, 529]], 
* Val   accuracy / confusion: 67.46% / [[127, 103], [89, 271]]

------------------------------ Epoch 193 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.165878
- Iter 028 / 029, Loss: 0.203514

* Train accuracy / confusion: 89.98% / [[313, 49], [44, 522]], 
* Val   accuracy / confusion: 63.22% / [[66, 164], [53, 307]]

------------------------------ Epoch 194 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.447083
- Iter 028 / 029, Loss: 0.149899

* Train accuracy / confusion: 91.38% / [[326, 34], [46, 522]], 
* Val   accuracy / confusion: 67.97% / [[143, 87], [102, 258]]

------------------------------ Epoch 195 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.188304
- Iter 028 / 029, Loss: 0.354513

* Train accuracy / confusion: 88.90% / [[312, 52], [51, 513]], 
* Val   accuracy / confusion: 69.15% / [[170, 60], [122, 238]]

------------------------------ Epoch 196 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.285534
- Iter 028 / 029, Loss: 0.245993

* Train accuracy / confusion: 88.15% / [[302, 58], [52, 516]], 
* Val   accuracy / confusion: 69.15% / [[156, 74], [108, 252]]

------------------------------ Epoch 197 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.299743
- Iter 028 / 029, Loss: 0.255037

* Train accuracy / confusion: 87.93% / [[302, 54], [58, 514]], 
* Val   accuracy / confusion: 67.97% / [[70, 160], [29, 331]]

------------------------------ Epoch 198 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.292798
- Iter 028 / 029, Loss: 0.247240

* Train accuracy / confusion: 90.30% / [[312, 45], [45, 526]], 
* Val   accuracy / confusion: 62.54% / [[180, 50], [171, 189]]

------------------------------ Epoch 199 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.150653
- Iter 028 / 029, Loss: 0.146133

* Train accuracy / confusion: 89.55% / [[316, 44], [53, 515]], 
* Val   accuracy / confusion: 71.02% / [[126, 104], [67, 293]]

------------------------------ Epoch 200 / 500, Learning rate: 1.49e-04 ------------------------------
- Iter 014 / 029, Loss: 0.221510
- Iter 028 / 029, Loss: 0.212695

* Train accuracy / confusion: 89.87% / [[316, 48], [46, 518]], 
* Val   accuracy / confusion: 67.29% / [[110, 120], [73, 287]]

------------------------------ Epoch 201 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.245681
- Iter 028 / 029, Loss: 0.198154

* Train accuracy / confusion: 90.62% / [[320, 43], [44, 521]], 
* Val   accuracy / confusion: 65.08% / [[114, 116], [90, 270]]

------------------------------ Epoch 202 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.216229
- Iter 028 / 029, Loss: 0.265782

* Train accuracy / confusion: 90.73% / [[314, 44], [42, 528]], 
* Val   accuracy / confusion: 66.95% / [[139, 91], [104, 256]]

------------------------------ Epoch 203 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.074399
- Iter 028 / 029, Loss: 0.267615

* Train accuracy / confusion: 93.32% / [[334, 29], [33, 532]], 
* Val   accuracy / confusion: 67.46% / [[137, 93], [99, 261]]

------------------------------ Epoch 204 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.197936
- Iter 028 / 029, Loss: 0.198080

* Train accuracy / confusion: 92.89% / [[321, 40], [26, 541]], 
* Val   accuracy / confusion: 69.83% / [[130, 100], [78, 282]]

------------------------------ Epoch 205 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.129473
- Iter 028 / 029, Loss: 0.150447

* Train accuracy / confusion: 93.21% / [[331, 30], [33, 534]], 
* Val   accuracy / confusion: 68.81% / [[131, 99], [85, 275]]

------------------------------ Epoch 206 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.130029
- Iter 028 / 029, Loss: 0.236175

* Train accuracy / confusion: 92.35% / [[332, 30], [41, 525]], 
* Val   accuracy / confusion: 66.95% / [[129, 101], [94, 266]]

------------------------------ Epoch 207 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.134315
- Iter 028 / 029, Loss: 0.195383

* Train accuracy / confusion: 91.16% / [[325, 36], [46, 521]], 
* Val   accuracy / confusion: 66.44% / [[135, 95], [103, 257]]

------------------------------ Epoch 208 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.146084
- Iter 028 / 029, Loss: 0.146233

* Train accuracy / confusion: 91.81% / [[321, 35], [41, 531]], 
* Val   accuracy / confusion: 65.59% / [[128, 102], [101, 259]]

------------------------------ Epoch 209 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.127071
- Iter 028 / 029, Loss: 0.222285

* Train accuracy / confusion: 93.32% / [[335, 27], [35, 531]], 
* Val   accuracy / confusion: 69.15% / [[135, 95], [87, 273]]

------------------------------ Epoch 210 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.148558
- Iter 028 / 029, Loss: 0.119990

* Train accuracy / confusion: 91.59% / [[328, 32], [46, 522]], 
* Val   accuracy / confusion: 66.27% / [[128, 102], [97, 263]]

------------------------------ Epoch 211 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.099962
- Iter 028 / 029, Loss: 0.158786

* Train accuracy / confusion: 92.67% / [[328, 32], [36, 532]], 
* Val   accuracy / confusion: 66.78% / [[125, 105], [91, 269]]

------------------------------ Epoch 212 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.188296
- Iter 028 / 029, Loss: 0.197790

* Train accuracy / confusion: 92.24% / [[323, 40], [32, 533]], 
* Val   accuracy / confusion: 67.29% / [[121, 109], [84, 276]]

------------------------------ Epoch 213 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.093040
- Iter 028 / 029, Loss: 0.124372

* Train accuracy / confusion: 92.46% / [[323, 40], [30, 535]], 
* Val   accuracy / confusion: 68.31% / [[132, 98], [89, 271]]

------------------------------ Epoch 214 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.096362
- Iter 028 / 029, Loss: 0.488023

* Train accuracy / confusion: 91.70% / [[320, 43], [34, 531]], 
* Val   accuracy / confusion: 68.64% / [[125, 105], [80, 280]]

------------------------------ Epoch 215 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.189497
- Iter 028 / 029, Loss: 0.276003

* Train accuracy / confusion: 94.07% / [[336, 25], [30, 537]], 
* Val   accuracy / confusion: 67.12% / [[125, 105], [89, 271]]

------------------------------ Epoch 216 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.125251
- Iter 028 / 029, Loss: 0.224155

* Train accuracy / confusion: 93.00% / [[333, 30], [35, 530]], 
* Val   accuracy / confusion: 66.78% / [[137, 93], [103, 257]]

------------------------------ Epoch 217 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.174248
- Iter 028 / 029, Loss: 0.237291

* Train accuracy / confusion: 92.67% / [[331, 34], [34, 529]], 
* Val   accuracy / confusion: 67.80% / [[122, 108], [82, 278]]

------------------------------ Epoch 218 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.120693
- Iter 028 / 029, Loss: 0.095341

* Train accuracy / confusion: 93.53% / [[321, 37], [23, 547]], 
* Val   accuracy / confusion: 66.61% / [[117, 113], [84, 276]]

------------------------------ Epoch 219 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.207671
- Iter 028 / 029, Loss: 0.270938

* Train accuracy / confusion: 93.75% / [[335, 27], [31, 535]], 
* Val   accuracy / confusion: 68.14% / [[132, 98], [90, 270]]

------------------------------ Epoch 220 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.073073
- Iter 028 / 029, Loss: 0.102357

* Train accuracy / confusion: 94.72% / [[342, 20], [29, 537]], 
* Val   accuracy / confusion: 70.17% / [[138, 92], [84, 276]]

------------------------------ Epoch 221 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.117605
- Iter 028 / 029, Loss: 0.175003

* Train accuracy / confusion: 93.53% / [[336, 30], [30, 532]], 
* Val   accuracy / confusion: 68.47% / [[114, 116], [70, 290]]

------------------------------ Epoch 222 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.172580
- Iter 028 / 029, Loss: 0.198927

* Train accuracy / confusion: 92.46% / [[326, 39], [31, 532]], 
* Val   accuracy / confusion: 72.03% / [[144, 86], [79, 281]]

------------------------------ Epoch 223 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.179086
- Iter 028 / 029, Loss: 0.277608

* Train accuracy / confusion: 93.86% / [[336, 27], [30, 535]], 
* Val   accuracy / confusion: 69.49% / [[139, 91], [89, 271]]

------------------------------ Epoch 224 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.172773
- Iter 028 / 029, Loss: 0.191333

* Train accuracy / confusion: 93.86% / [[343, 18], [39, 528]], 
* Val   accuracy / confusion: 69.15% / [[142, 88], [94, 266]]

------------------------------ Epoch 225 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.166858
- Iter 028 / 029, Loss: 0.178868

* Train accuracy / confusion: 92.67% / [[331, 30], [38, 529]], 
* Val   accuracy / confusion: 70.34% / [[138, 92], [83, 277]]

------------------------------ Epoch 226 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.166488
- Iter 028 / 029, Loss: 0.113830

* Train accuracy / confusion: 93.43% / [[324, 31], [30, 543]], 
* Val   accuracy / confusion: 65.76% / [[133, 97], [105, 255]]

------------------------------ Epoch 227 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.306722
- Iter 028 / 029, Loss: 0.246319

* Train accuracy / confusion: 91.38% / [[325, 38], [42, 523]], 
* Val   accuracy / confusion: 67.46% / [[124, 106], [86, 274]]

------------------------------ Epoch 228 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.182264
- Iter 028 / 029, Loss: 0.085696

* Train accuracy / confusion: 92.46% / [[329, 34], [36, 529]], 
* Val   accuracy / confusion: 68.64% / [[127, 103], [82, 278]]

------------------------------ Epoch 229 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.163424
- Iter 028 / 029, Loss: 0.072657

* Train accuracy / confusion: 93.43% / [[329, 31], [30, 538]], 
* Val   accuracy / confusion: 67.12% / [[122, 108], [86, 274]]

------------------------------ Epoch 230 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.104993
- Iter 028 / 029, Loss: 0.097346

* Train accuracy / confusion: 93.43% / [[334, 32], [29, 533]], 
* Val   accuracy / confusion: 64.92% / [[118, 112], [95, 265]]

------------------------------ Epoch 231 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.203788
- Iter 028 / 029, Loss: 0.136441

* Train accuracy / confusion: 92.13% / [[325, 34], [39, 530]], 
* Val   accuracy / confusion: 66.78% / [[135, 95], [101, 259]]

------------------------------ Epoch 232 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.442221
- Iter 028 / 029, Loss: 0.082997

* Train accuracy / confusion: 92.46% / [[326, 34], [36, 532]], 
* Val   accuracy / confusion: 66.61% / [[127, 103], [94, 266]]

------------------------------ Epoch 233 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.161982
- Iter 028 / 029, Loss: 0.372716

* Train accuracy / confusion: 92.56% / [[327, 36], [33, 532]], 
* Val   accuracy / confusion: 71.86% / [[137, 93], [73, 287]]

------------------------------ Epoch 234 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.276014
- Iter 028 / 029, Loss: 0.137623

* Train accuracy / confusion: 92.78% / [[332, 31], [36, 529]], 
* Val   accuracy / confusion: 67.80% / [[133, 97], [93, 267]]

------------------------------ Epoch 235 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.398964
- Iter 028 / 029, Loss: 0.119960

* Train accuracy / confusion: 93.75% / [[332, 32], [26, 538]], 
* Val   accuracy / confusion: 68.64% / [[138, 92], [93, 267]]

------------------------------ Epoch 236 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.206756
- Iter 028 / 029, Loss: 0.155077

* Train accuracy / confusion: 93.21% / [[335, 27], [36, 530]], 
* Val   accuracy / confusion: 67.80% / [[125, 105], [85, 275]]

------------------------------ Epoch 237 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.133101
- Iter 028 / 029, Loss: 0.135502

* Train accuracy / confusion: 92.35% / [[332, 31], [40, 525]], 
* Val   accuracy / confusion: 67.12% / [[139, 91], [103, 257]]

------------------------------ Epoch 238 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.214141
- Iter 028 / 029, Loss: 0.099601

* Train accuracy / confusion: 93.00% / [[334, 29], [36, 529]], 
* Val   accuracy / confusion: 68.98% / [[144, 86], [97, 263]]

------------------------------ Epoch 239 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.127974
- Iter 028 / 029, Loss: 0.338738

* Train accuracy / confusion: 94.50% / [[337, 22], [29, 540]], 
* Val   accuracy / confusion: 67.80% / [[124, 106], [84, 276]]

------------------------------ Epoch 240 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.119655
- Iter 028 / 029, Loss: 0.101119

* Train accuracy / confusion: 93.97% / [[339, 25], [31, 533]], 
* Val   accuracy / confusion: 66.61% / [[130, 100], [97, 263]]

------------------------------ Epoch 241 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.204424
- Iter 028 / 029, Loss: 0.172048

* Train accuracy / confusion: 93.32% / [[335, 29], [33, 531]], 
* Val   accuracy / confusion: 68.64% / [[136, 94], [91, 269]]

------------------------------ Epoch 242 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.173742
- Iter 028 / 029, Loss: 0.065725

* Train accuracy / confusion: 92.67% / [[330, 36], [32, 530]], 
* Val   accuracy / confusion: 68.81% / [[123, 107], [77, 283]]

------------------------------ Epoch 243 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.152816
- Iter 028 / 029, Loss: 0.163276

* Train accuracy / confusion: 92.46% / [[329, 36], [34, 529]], 
* Val   accuracy / confusion: 66.10% / [[115, 115], [85, 275]]

------------------------------ Epoch 244 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.152566
- Iter 028 / 029, Loss: 0.079197

* Train accuracy / confusion: 94.50% / [[338, 26], [25, 539]], 
* Val   accuracy / confusion: 70.34% / [[139, 91], [84, 276]]

------------------------------ Epoch 245 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.222750
- Iter 028 / 029, Loss: 0.149120

* Train accuracy / confusion: 92.78% / [[327, 37], [30, 534]], 
* Val   accuracy / confusion: 67.12% / [[123, 107], [87, 273]]

------------------------------ Epoch 246 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.168424
- Iter 028 / 029, Loss: 0.098889

* Train accuracy / confusion: 94.29% / [[336, 24], [29, 539]], 
* Val   accuracy / confusion: 70.00% / [[136, 94], [83, 277]]

------------------------------ Epoch 247 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.187425
- Iter 028 / 029, Loss: 0.176582

* Train accuracy / confusion: 93.00% / [[336, 26], [39, 527]], 
* Val   accuracy / confusion: 69.66% / [[142, 88], [91, 269]]

------------------------------ Epoch 248 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.117041
- Iter 028 / 029, Loss: 0.108389

* Train accuracy / confusion: 92.78% / [[326, 38], [29, 535]], 
* Val   accuracy / confusion: 70.68% / [[134, 96], [77, 283]]

------------------------------ Epoch 249 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.107712
- Iter 028 / 029, Loss: 0.108915

* Train accuracy / confusion: 93.86% / [[334, 27], [30, 537]], 
* Val   accuracy / confusion: 68.81% / [[152, 78], [106, 254]]

------------------------------ Epoch 250 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.199921
- Iter 028 / 029, Loss: 0.073311

* Train accuracy / confusion: 93.97% / [[336, 25], [31, 536]], 
* Val   accuracy / confusion: 65.76% / [[115, 115], [87, 273]]

------------------------------ Epoch 251 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.151570
- Iter 028 / 029, Loss: 0.105981

* Train accuracy / confusion: 93.75% / [[335, 27], [31, 535]], 
* Val   accuracy / confusion: 67.46% / [[130, 100], [92, 268]]

------------------------------ Epoch 252 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.277553
- Iter 028 / 029, Loss: 0.052066

* Train accuracy / confusion: 94.18% / [[332, 30], [24, 542]], 
* Val   accuracy / confusion: 68.64% / [[138, 92], [93, 267]]

------------------------------ Epoch 253 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.104339
- Iter 028 / 029, Loss: 0.201691

* Train accuracy / confusion: 94.29% / [[335, 28], [25, 540]], 
* Val   accuracy / confusion: 70.68% / [[142, 88], [85, 275]]

------------------------------ Epoch 254 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.073859
- Iter 028 / 029, Loss: 0.095009

* Train accuracy / confusion: 94.40% / [[339, 24], [28, 537]], 
* Val   accuracy / confusion: 67.63% / [[134, 96], [95, 265]]

------------------------------ Epoch 255 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.078362
- Iter 028 / 029, Loss: 0.065202

* Train accuracy / confusion: 94.61% / [[341, 26], [24, 537]], 
* Val   accuracy / confusion: 67.29% / [[131, 99], [94, 266]]

------------------------------ Epoch 256 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.320556
- Iter 028 / 029, Loss: 0.203148

* Train accuracy / confusion: 93.00% / [[330, 31], [34, 533]], 
* Val   accuracy / confusion: 66.10% / [[105, 125], [75, 285]]

------------------------------ Epoch 257 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.299358
- Iter 028 / 029, Loss: 0.118433

* Train accuracy / confusion: 93.00% / [[332, 28], [37, 531]], 
* Val   accuracy / confusion: 65.42% / [[134, 96], [108, 252]]

------------------------------ Epoch 258 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.277803
- Iter 028 / 029, Loss: 0.203415

* Train accuracy / confusion: 93.43% / [[331, 31], [30, 536]], 
* Val   accuracy / confusion: 68.14% / [[136, 94], [94, 266]]

------------------------------ Epoch 259 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.290558
- Iter 028 / 029, Loss: 0.113204

* Train accuracy / confusion: 94.29% / [[338, 23], [30, 537]], 
* Val   accuracy / confusion: 70.68% / [[147, 83], [90, 270]]

------------------------------ Epoch 260 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.062951
- Iter 028 / 029, Loss: 0.124209

* Train accuracy / confusion: 94.50% / [[337, 24], [27, 540]], 
* Val   accuracy / confusion: 68.98% / [[127, 103], [80, 280]]

------------------------------ Epoch 261 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.208319
- Iter 028 / 029, Loss: 0.208305

* Train accuracy / confusion: 93.10% / [[331, 30], [34, 533]], 
* Val   accuracy / confusion: 67.63% / [[128, 102], [89, 271]]

------------------------------ Epoch 262 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.237891
- Iter 028 / 029, Loss: 0.045795

* Train accuracy / confusion: 95.26% / [[336, 26], [18, 548]], 
* Val   accuracy / confusion: 68.81% / [[127, 103], [81, 279]]

------------------------------ Epoch 263 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.115186
- Iter 028 / 029, Loss: 0.095934

* Train accuracy / confusion: 94.72% / [[337, 25], [24, 542]], 
* Val   accuracy / confusion: 69.32% / [[156, 74], [107, 253]]

------------------------------ Epoch 264 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.297355
- Iter 028 / 029, Loss: 0.174365

* Train accuracy / confusion: 93.97% / [[335, 27], [29, 537]], 
* Val   accuracy / confusion: 68.14% / [[137, 93], [95, 265]]

------------------------------ Epoch 265 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.115095
- Iter 028 / 029, Loss: 0.080321

* Train accuracy / confusion: 94.29% / [[344, 21], [32, 531]], 
* Val   accuracy / confusion: 65.08% / [[138, 92], [114, 246]]

------------------------------ Epoch 266 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.135070
- Iter 028 / 029, Loss: 0.061624

* Train accuracy / confusion: 93.10% / [[332, 32], [32, 532]], 
* Val   accuracy / confusion: 69.49% / [[141, 89], [91, 269]]

------------------------------ Epoch 267 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.236065
- Iter 028 / 029, Loss: 0.151892

* Train accuracy / confusion: 94.72% / [[338, 25], [24, 541]], 
* Val   accuracy / confusion: 67.97% / [[125, 105], [84, 276]]

------------------------------ Epoch 268 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.108909
- Iter 028 / 029, Loss: 0.145750

* Train accuracy / confusion: 95.15% / [[338, 25], [20, 545]], 
* Val   accuracy / confusion: 68.81% / [[137, 93], [91, 269]]

------------------------------ Epoch 269 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.277018
- Iter 028 / 029, Loss: 0.058410

* Train accuracy / confusion: 94.72% / [[339, 25], [24, 540]], 
* Val   accuracy / confusion: 68.64% / [[125, 105], [80, 280]]

------------------------------ Epoch 270 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.217578
- Iter 028 / 029, Loss: 0.120649

* Train accuracy / confusion: 93.10% / [[337, 28], [36, 527]], 
* Val   accuracy / confusion: 66.78% / [[137, 93], [103, 257]]

------------------------------ Epoch 271 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.180174
- Iter 028 / 029, Loss: 0.315283

* Train accuracy / confusion: 93.53% / [[330, 31], [29, 538]], 
* Val   accuracy / confusion: 69.49% / [[135, 95], [85, 275]]

------------------------------ Epoch 272 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.078259
- Iter 028 / 029, Loss: 0.319443

* Train accuracy / confusion: 94.72% / [[343, 22], [27, 536]], 
* Val   accuracy / confusion: 69.32% / [[147, 83], [98, 262]]

------------------------------ Epoch 273 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.110773
- Iter 028 / 029, Loss: 0.285653

* Train accuracy / confusion: 92.67% / [[326, 36], [32, 534]], 
* Val   accuracy / confusion: 69.66% / [[155, 75], [104, 256]]

------------------------------ Epoch 274 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.247294
- Iter 028 / 029, Loss: 0.077319

* Train accuracy / confusion: 93.43% / [[337, 26], [35, 530]], 
* Val   accuracy / confusion: 66.95% / [[125, 105], [90, 270]]

------------------------------ Epoch 275 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.141183
- Iter 028 / 029, Loss: 0.260665

* Train accuracy / confusion: 94.18% / [[337, 26], [28, 537]], 
* Val   accuracy / confusion: 68.14% / [[145, 85], [103, 257]]

------------------------------ Epoch 276 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.072999
- Iter 028 / 029, Loss: 0.079498

* Train accuracy / confusion: 94.72% / [[340, 19], [30, 539]], 
* Val   accuracy / confusion: 68.31% / [[138, 92], [95, 265]]

------------------------------ Epoch 277 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.347883
- Iter 028 / 029, Loss: 0.280137

* Train accuracy / confusion: 93.75% / [[330, 32], [26, 540]], 
* Val   accuracy / confusion: 69.83% / [[137, 93], [85, 275]]

------------------------------ Epoch 278 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.116975
- Iter 028 / 029, Loss: 0.221052

* Train accuracy / confusion: 93.21% / [[333, 28], [35, 532]], 
* Val   accuracy / confusion: 66.61% / [[110, 120], [77, 283]]

------------------------------ Epoch 279 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.077119
- Iter 028 / 029, Loss: 0.135796

* Train accuracy / confusion: 93.21% / [[338, 25], [38, 527]], 
* Val   accuracy / confusion: 67.46% / [[141, 89], [103, 257]]

------------------------------ Epoch 280 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.260878
- Iter 028 / 029, Loss: 0.194193

* Train accuracy / confusion: 93.43% / [[329, 33], [28, 538]], 
* Val   accuracy / confusion: 69.32% / [[133, 97], [84, 276]]

------------------------------ Epoch 281 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.207053
- Iter 028 / 029, Loss: 0.130438

* Train accuracy / confusion: 94.61% / [[339, 20], [30, 539]], 
* Val   accuracy / confusion: 70.00% / [[142, 88], [89, 271]]

------------------------------ Epoch 282 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.077966
- Iter 028 / 029, Loss: 0.111798

* Train accuracy / confusion: 93.21% / [[332, 29], [34, 533]], 
* Val   accuracy / confusion: 68.81% / [[138, 92], [92, 268]]

------------------------------ Epoch 283 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.243016
- Iter 028 / 029, Loss: 0.174231

* Train accuracy / confusion: 93.86% / [[340, 25], [32, 531]], 
* Val   accuracy / confusion: 68.64% / [[125, 105], [80, 280]]

------------------------------ Epoch 284 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.077370
- Iter 028 / 029, Loss: 0.185974

* Train accuracy / confusion: 92.24% / [[332, 28], [44, 524]], 
* Val   accuracy / confusion: 67.97% / [[136, 94], [95, 265]]

------------------------------ Epoch 285 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.316600
- Iter 028 / 029, Loss: 0.195194

* Train accuracy / confusion: 93.43% / [[334, 27], [34, 533]], 
* Val   accuracy / confusion: 65.93% / [[132, 98], [103, 257]]

------------------------------ Epoch 286 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.096211
- Iter 028 / 029, Loss: 0.252363

* Train accuracy / confusion: 93.10% / [[331, 33], [31, 533]], 
* Val   accuracy / confusion: 67.12% / [[132, 98], [96, 264]]

------------------------------ Epoch 287 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.078949
- Iter 028 / 029, Loss: 0.304050

* Train accuracy / confusion: 94.40% / [[337, 29], [23, 539]], 
* Val   accuracy / confusion: 68.14% / [[145, 85], [103, 257]]

------------------------------ Epoch 288 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.201475
- Iter 028 / 029, Loss: 0.201610

* Train accuracy / confusion: 93.43% / [[333, 29], [32, 534]], 
* Val   accuracy / confusion: 68.64% / [[130, 100], [85, 275]]

------------------------------ Epoch 289 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.590672
- Iter 028 / 029, Loss: 0.254582

* Train accuracy / confusion: 93.97% / [[339, 25], [31, 533]], 
* Val   accuracy / confusion: 66.61% / [[129, 101], [96, 264]]

------------------------------ Epoch 290 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.085779
- Iter 028 / 029, Loss: 0.179386

* Train accuracy / confusion: 94.07% / [[338, 29], [26, 535]], 
* Val   accuracy / confusion: 69.15% / [[138, 92], [90, 270]]

------------------------------ Epoch 291 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.149406
- Iter 028 / 029, Loss: 0.064092

* Train accuracy / confusion: 95.58% / [[346, 14], [27, 541]], 
* Val   accuracy / confusion: 69.83% / [[151, 79], [99, 261]]

------------------------------ Epoch 292 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.174605
- Iter 028 / 029, Loss: 0.145145

* Train accuracy / confusion: 94.94% / [[334, 28], [19, 547]], 
* Val   accuracy / confusion: 68.47% / [[139, 91], [95, 265]]

------------------------------ Epoch 293 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.203311
- Iter 028 / 029, Loss: 0.119308

* Train accuracy / confusion: 94.40% / [[335, 29], [23, 541]], 
* Val   accuracy / confusion: 67.97% / [[134, 96], [93, 267]]

------------------------------ Epoch 294 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.270751
- Iter 028 / 029, Loss: 0.050436

* Train accuracy / confusion: 93.53% / [[333, 29], [31, 535]], 
* Val   accuracy / confusion: 68.31% / [[124, 106], [81, 279]]

------------------------------ Epoch 295 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.085420
- Iter 028 / 029, Loss: 0.103432

* Train accuracy / confusion: 93.64% / [[334, 27], [32, 535]], 
* Val   accuracy / confusion: 70.68% / [[151, 79], [94, 266]]

------------------------------ Epoch 296 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.162707
- Iter 028 / 029, Loss: 0.167908

* Train accuracy / confusion: 94.18% / [[342, 21], [33, 532]], 
* Val   accuracy / confusion: 70.68% / [[146, 84], [89, 271]]

------------------------------ Epoch 297 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.195168
- Iter 028 / 029, Loss: 0.171942

* Train accuracy / confusion: 94.40% / [[332, 25], [27, 544]], 
* Val   accuracy / confusion: 68.98% / [[135, 95], [88, 272]]

------------------------------ Epoch 298 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.173031
- Iter 028 / 029, Loss: 0.118620

* Train accuracy / confusion: 94.72% / [[337, 23], [26, 542]], 
* Val   accuracy / confusion: 67.80% / [[121, 109], [81, 279]]

------------------------------ Epoch 299 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.071360
- Iter 028 / 029, Loss: 0.224990

* Train accuracy / confusion: 95.80% / [[347, 17], [22, 542]], 
* Val   accuracy / confusion: 69.83% / [[140, 90], [88, 272]]

------------------------------ Epoch 300 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.131423
- Iter 028 / 029, Loss: 0.200167

* Train accuracy / confusion: 95.15% / [[342, 21], [24, 541]], 
* Val   accuracy / confusion: 71.19% / [[133, 97], [73, 287]]

------------------------------ Epoch 301 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.157800
- Iter 028 / 029, Loss: 0.105528

* Train accuracy / confusion: 95.58% / [[347, 15], [26, 540]], 
* Val   accuracy / confusion: 70.51% / [[136, 94], [80, 280]]

------------------------------ Epoch 302 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.122555
- Iter 028 / 029, Loss: 0.076210

* Train accuracy / confusion: 94.72% / [[332, 28], [21, 547]], 
* Val   accuracy / confusion: 67.97% / [[143, 87], [102, 258]]

------------------------------ Epoch 303 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.256020
- Iter 028 / 029, Loss: 0.143792

* Train accuracy / confusion: 95.15% / [[343, 19], [26, 540]], 
* Val   accuracy / confusion: 70.17% / [[132, 98], [78, 282]]

------------------------------ Epoch 304 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.048430
- Iter 028 / 029, Loss: 0.099909

* Train accuracy / confusion: 96.12% / [[349, 15], [21, 543]], 
* Val   accuracy / confusion: 69.66% / [[139, 91], [88, 272]]

------------------------------ Epoch 305 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.109072
- Iter 028 / 029, Loss: 0.067421

* Train accuracy / confusion: 95.37% / [[341, 21], [22, 544]], 
* Val   accuracy / confusion: 68.47% / [[130, 100], [86, 274]]

------------------------------ Epoch 306 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.175473
- Iter 028 / 029, Loss: 0.113788

* Train accuracy / confusion: 94.29% / [[335, 27], [26, 540]], 
* Val   accuracy / confusion: 67.80% / [[129, 101], [89, 271]]

------------------------------ Epoch 307 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.236776
- Iter 028 / 029, Loss: 0.223446

* Train accuracy / confusion: 93.97% / [[339, 24], [32, 533]], 
* Val   accuracy / confusion: 67.97% / [[126, 104], [85, 275]]

------------------------------ Epoch 308 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.086244
- Iter 028 / 029, Loss: 0.118402

* Train accuracy / confusion: 96.23% / [[343, 15], [20, 550]], 
* Val   accuracy / confusion: 68.64% / [[121, 109], [76, 284]]

------------------------------ Epoch 309 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.097376
- Iter 028 / 029, Loss: 0.066914

* Train accuracy / confusion: 94.72% / [[342, 20], [29, 537]], 
* Val   accuracy / confusion: 68.47% / [[135, 95], [91, 269]]

------------------------------ Epoch 310 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.079346
- Iter 028 / 029, Loss: 0.110280

* Train accuracy / confusion: 93.97% / [[336, 26], [30, 536]], 
* Val   accuracy / confusion: 68.81% / [[138, 92], [92, 268]]

------------------------------ Epoch 311 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.313493
- Iter 028 / 029, Loss: 0.078328

* Train accuracy / confusion: 94.94% / [[336, 24], [23, 545]], 
* Val   accuracy / confusion: 67.12% / [[124, 106], [88, 272]]

------------------------------ Epoch 312 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.068824
- Iter 028 / 029, Loss: 0.129002

* Train accuracy / confusion: 94.29% / [[338, 26], [27, 537]], 
* Val   accuracy / confusion: 67.46% / [[138, 92], [100, 260]]

------------------------------ Epoch 313 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.172609
- Iter 028 / 029, Loss: 0.180219

* Train accuracy / confusion: 93.86% / [[334, 29], [28, 537]], 
* Val   accuracy / confusion: 67.12% / [[149, 81], [113, 247]]

------------------------------ Epoch 314 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.175417
- Iter 028 / 029, Loss: 0.178459

* Train accuracy / confusion: 94.50% / [[332, 27], [24, 545]], 
* Val   accuracy / confusion: 66.95% / [[120, 110], [85, 275]]

------------------------------ Epoch 315 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.170634
- Iter 028 / 029, Loss: 0.077409

* Train accuracy / confusion: 93.97% / [[332, 28], [28, 540]], 
* Val   accuracy / confusion: 68.98% / [[142, 88], [95, 265]]

------------------------------ Epoch 316 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.169219
- Iter 028 / 029, Loss: 0.098813

* Train accuracy / confusion: 94.94% / [[338, 20], [27, 543]], 
* Val   accuracy / confusion: 68.64% / [[118, 112], [73, 287]]

------------------------------ Epoch 317 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.145134
- Iter 028 / 029, Loss: 0.090209

* Train accuracy / confusion: 94.18% / [[338, 28], [26, 536]], 
* Val   accuracy / confusion: 66.61% / [[129, 101], [96, 264]]

------------------------------ Epoch 318 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.058477
- Iter 028 / 029, Loss: 0.051637

* Train accuracy / confusion: 94.83% / [[350, 13], [35, 530]], 
* Val   accuracy / confusion: 70.85% / [[141, 89], [83, 277]]

------------------------------ Epoch 319 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.271114
- Iter 028 / 029, Loss: 0.177126

* Train accuracy / confusion: 94.07% / [[330, 30], [25, 543]], 
* Val   accuracy / confusion: 69.32% / [[145, 85], [96, 264]]

------------------------------ Epoch 320 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.133740
- Iter 028 / 029, Loss: 0.242708

* Train accuracy / confusion: 94.18% / [[334, 26], [28, 540]], 
* Val   accuracy / confusion: 68.14% / [[135, 95], [93, 267]]

------------------------------ Epoch 321 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.036527
- Iter 028 / 029, Loss: 0.158961

* Train accuracy / confusion: 94.40% / [[333, 25], [27, 543]], 
* Val   accuracy / confusion: 67.80% / [[140, 90], [100, 260]]

------------------------------ Epoch 322 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.070658
- Iter 028 / 029, Loss: 0.189199

* Train accuracy / confusion: 95.26% / [[344, 22], [22, 540]], 
* Val   accuracy / confusion: 69.66% / [[128, 102], [77, 283]]

------------------------------ Epoch 323 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.087127
- Iter 028 / 029, Loss: 0.154455

* Train accuracy / confusion: 95.26% / [[344, 19], [25, 540]], 
* Val   accuracy / confusion: 67.46% / [[131, 99], [93, 267]]

------------------------------ Epoch 324 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.148468
- Iter 028 / 029, Loss: 0.142296

* Train accuracy / confusion: 94.72% / [[339, 26], [23, 540]], 
* Val   accuracy / confusion: 65.93% / [[119, 111], [90, 270]]

------------------------------ Epoch 325 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.160859
- Iter 028 / 029, Loss: 0.304181

* Train accuracy / confusion: 93.86% / [[336, 28], [29, 535]], 
* Val   accuracy / confusion: 67.63% / [[138, 92], [99, 261]]

------------------------------ Epoch 326 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.046102
- Iter 028 / 029, Loss: 0.182175

* Train accuracy / confusion: 95.15% / [[340, 25], [20, 543]], 
* Val   accuracy / confusion: 68.98% / [[121, 109], [74, 286]]

------------------------------ Epoch 327 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.170250
- Iter 028 / 029, Loss: 0.063622

* Train accuracy / confusion: 94.40% / [[338, 26], [26, 538]], 
* Val   accuracy / confusion: 68.31% / [[136, 94], [93, 267]]

------------------------------ Epoch 328 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.066311
- Iter 028 / 029, Loss: 0.125233

* Train accuracy / confusion: 94.94% / [[344, 18], [29, 537]], 
* Val   accuracy / confusion: 68.14% / [[137, 93], [95, 265]]

------------------------------ Epoch 329 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.135147
- Iter 028 / 029, Loss: 0.096664

* Train accuracy / confusion: 96.12% / [[345, 20], [16, 547]], 
* Val   accuracy / confusion: 65.25% / [[119, 111], [94, 266]]

------------------------------ Epoch 330 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.067254
- Iter 028 / 029, Loss: 0.150719

* Train accuracy / confusion: 95.58% / [[339, 20], [21, 548]], 
* Val   accuracy / confusion: 66.27% / [[135, 95], [104, 256]]

------------------------------ Epoch 331 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.102575
- Iter 028 / 029, Loss: 0.073127

* Train accuracy / confusion: 94.94% / [[342, 22], [25, 539]], 
* Val   accuracy / confusion: 68.47% / [[141, 89], [97, 263]]

------------------------------ Epoch 332 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.121672
- Iter 028 / 029, Loss: 0.183077

* Train accuracy / confusion: 94.83% / [[335, 26], [22, 545]], 
* Val   accuracy / confusion: 68.14% / [[137, 93], [95, 265]]

------------------------------ Epoch 333 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.169130
- Iter 028 / 029, Loss: 0.221433

* Train accuracy / confusion: 94.83% / [[346, 19], [29, 534]], 
* Val   accuracy / confusion: 68.81% / [[137, 93], [91, 269]]

------------------------------ Epoch 334 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.185612
- Iter 028 / 029, Loss: 0.160654

* Train accuracy / confusion: 94.40% / [[333, 28], [24, 543]], 
* Val   accuracy / confusion: 67.97% / [[142, 88], [101, 259]]

------------------------------ Epoch 335 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.073506
- Iter 028 / 029, Loss: 0.121337

* Train accuracy / confusion: 95.15% / [[345, 19], [26, 538]], 
* Val   accuracy / confusion: 65.76% / [[110, 120], [82, 278]]

------------------------------ Epoch 336 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.058193
- Iter 028 / 029, Loss: 0.132189

* Train accuracy / confusion: 95.47% / [[338, 19], [23, 548]], 
* Val   accuracy / confusion: 66.95% / [[130, 100], [95, 265]]

------------------------------ Epoch 337 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.105728
- Iter 028 / 029, Loss: 0.219411

* Train accuracy / confusion: 94.50% / [[336, 26], [25, 541]], 
* Val   accuracy / confusion: 67.46% / [[142, 88], [104, 256]]

------------------------------ Epoch 338 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.098872
- Iter 028 / 029, Loss: 0.074654

* Train accuracy / confusion: 94.40% / [[338, 25], [27, 538]], 
* Val   accuracy / confusion: 68.81% / [[135, 95], [89, 271]]

------------------------------ Epoch 339 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.120200
- Iter 028 / 029, Loss: 0.108809

* Train accuracy / confusion: 93.75% / [[335, 29], [29, 535]], 
* Val   accuracy / confusion: 70.00% / [[129, 101], [76, 284]]

------------------------------ Epoch 340 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.211037
- Iter 028 / 029, Loss: 0.137453

* Train accuracy / confusion: 95.04% / [[339, 23], [23, 543]], 
* Val   accuracy / confusion: 67.80% / [[136, 94], [96, 264]]

------------------------------ Epoch 341 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.133986
- Iter 028 / 029, Loss: 0.058359

* Train accuracy / confusion: 96.34% / [[347, 15], [19, 547]], 
* Val   accuracy / confusion: 68.31% / [[143, 87], [100, 260]]

------------------------------ Epoch 342 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.107019
- Iter 028 / 029, Loss: 0.077239

* Train accuracy / confusion: 95.58% / [[353, 14], [27, 534]], 
* Val   accuracy / confusion: 68.14% / [[117, 113], [75, 285]]

------------------------------ Epoch 343 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.093837
- Iter 028 / 029, Loss: 0.068568

* Train accuracy / confusion: 95.47% / [[335, 25], [17, 551]], 
* Val   accuracy / confusion: 66.61% / [[130, 100], [97, 263]]

------------------------------ Epoch 344 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.108102
- Iter 028 / 029, Loss: 0.080271

* Train accuracy / confusion: 95.58% / [[342, 18], [23, 545]], 
* Val   accuracy / confusion: 67.80% / [[141, 89], [101, 259]]

------------------------------ Epoch 345 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.059575
- Iter 028 / 029, Loss: 0.096957

* Train accuracy / confusion: 95.26% / [[342, 21], [23, 542]], 
* Val   accuracy / confusion: 67.46% / [[149, 81], [111, 249]]

------------------------------ Epoch 346 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.046525
- Iter 028 / 029, Loss: 0.050251

* Train accuracy / confusion: 96.12% / [[345, 19], [17, 547]], 
* Val   accuracy / confusion: 66.95% / [[136, 94], [101, 259]]

------------------------------ Epoch 347 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.056685
- Iter 028 / 029, Loss: 0.186959

* Train accuracy / confusion: 95.58% / [[346, 17], [24, 541]], 
* Val   accuracy / confusion: 67.29% / [[128, 102], [91, 269]]

------------------------------ Epoch 348 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.235084
- Iter 028 / 029, Loss: 0.054753

* Train accuracy / confusion: 94.61% / [[338, 24], [26, 540]], 
* Val   accuracy / confusion: 71.02% / [[147, 83], [88, 272]]

------------------------------ Epoch 349 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.175035
- Iter 028 / 029, Loss: 0.082441

* Train accuracy / confusion: 94.07% / [[338, 26], [29, 535]], 
* Val   accuracy / confusion: 67.29% / [[139, 91], [102, 258]]

------------------------------ Epoch 350 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.202007
- Iter 028 / 029, Loss: 0.134148

* Train accuracy / confusion: 95.47% / [[348, 15], [27, 538]], 
* Val   accuracy / confusion: 66.78% / [[131, 99], [97, 263]]

------------------------------ Epoch 351 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.190650
- Iter 028 / 029, Loss: 0.183202

* Train accuracy / confusion: 96.23% / [[343, 19], [16, 550]], 
* Val   accuracy / confusion: 68.14% / [[140, 90], [98, 262]]

------------------------------ Epoch 352 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.065578
- Iter 028 / 029, Loss: 0.065612

* Train accuracy / confusion: 96.12% / [[345, 17], [19, 547]], 
* Val   accuracy / confusion: 66.78% / [[130, 100], [96, 264]]

------------------------------ Epoch 353 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.106928
- Iter 028 / 029, Loss: 0.167719

* Train accuracy / confusion: 93.97% / [[337, 24], [32, 535]], 
* Val   accuracy / confusion: 66.61% / [[126, 104], [93, 267]]

------------------------------ Epoch 354 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.097796
- Iter 028 / 029, Loss: 0.080782

* Train accuracy / confusion: 94.72% / [[342, 22], [27, 537]], 
* Val   accuracy / confusion: 70.68% / [[141, 89], [84, 276]]

------------------------------ Epoch 355 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.196650
- Iter 028 / 029, Loss: 0.200540

* Train accuracy / confusion: 94.40% / [[336, 26], [26, 540]], 
* Val   accuracy / confusion: 66.78% / [[123, 107], [89, 271]]

------------------------------ Epoch 356 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.256326
- Iter 028 / 029, Loss: 0.121626

* Train accuracy / confusion: 94.29% / [[345, 17], [36, 530]], 
* Val   accuracy / confusion: 69.32% / [[136, 94], [87, 273]]

------------------------------ Epoch 357 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.064684
- Iter 028 / 029, Loss: 0.054569

* Train accuracy / confusion: 95.69% / [[344, 19], [21, 544]], 
* Val   accuracy / confusion: 65.93% / [[123, 107], [94, 266]]

------------------------------ Epoch 358 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.057747
- Iter 028 / 029, Loss: 0.292493

* Train accuracy / confusion: 93.64% / [[335, 26], [33, 534]], 
* Val   accuracy / confusion: 66.78% / [[133, 97], [99, 261]]

------------------------------ Epoch 359 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.101065
- Iter 028 / 029, Loss: 0.185591

* Train accuracy / confusion: 94.72% / [[340, 24], [25, 539]], 
* Val   accuracy / confusion: 68.31% / [[122, 108], [79, 281]]

------------------------------ Epoch 360 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.169358
- Iter 028 / 029, Loss: 0.072201

* Train accuracy / confusion: 96.66% / [[346, 15], [16, 551]], 
* Val   accuracy / confusion: 67.46% / [[141, 89], [103, 257]]

------------------------------ Epoch 361 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.118681
- Iter 028 / 029, Loss: 0.059454

* Train accuracy / confusion: 95.91% / [[341, 19], [19, 549]], 
* Val   accuracy / confusion: 65.93% / [[107, 123], [78, 282]]

------------------------------ Epoch 362 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.135931
- Iter 028 / 029, Loss: 0.131474

* Train accuracy / confusion: 95.37% / [[341, 21], [22, 544]], 
* Val   accuracy / confusion: 68.98% / [[136, 94], [89, 271]]

------------------------------ Epoch 363 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.091462
- Iter 028 / 029, Loss: 0.080713

* Train accuracy / confusion: 96.44% / [[344, 15], [18, 551]], 
* Val   accuracy / confusion: 69.15% / [[146, 84], [98, 262]]

------------------------------ Epoch 364 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.165153
- Iter 028 / 029, Loss: 0.344864

* Train accuracy / confusion: 93.86% / [[339, 27], [30, 532]], 
* Val   accuracy / confusion: 68.31% / [[127, 103], [84, 276]]

------------------------------ Epoch 365 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.044118
- Iter 028 / 029, Loss: 0.159186

* Train accuracy / confusion: 95.15% / [[341, 21], [24, 542]], 
* Val   accuracy / confusion: 66.78% / [[118, 112], [84, 276]]

------------------------------ Epoch 366 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.277915
- Iter 028 / 029, Loss: 0.136028

* Train accuracy / confusion: 95.80% / [[344, 16], [23, 545]], 
* Val   accuracy / confusion: 66.10% / [[124, 106], [94, 266]]

------------------------------ Epoch 367 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.105249
- Iter 028 / 029, Loss: 0.122580

* Train accuracy / confusion: 95.15% / [[344, 19], [26, 539]], 
* Val   accuracy / confusion: 68.31% / [[147, 83], [104, 256]]

------------------------------ Epoch 368 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.152438
- Iter 028 / 029, Loss: 0.152309

* Train accuracy / confusion: 95.26% / [[341, 23], [21, 543]], 
* Val   accuracy / confusion: 69.32% / [[123, 107], [74, 286]]

------------------------------ Epoch 369 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.070277
- Iter 028 / 029, Loss: 0.066638

* Train accuracy / confusion: 95.47% / [[345, 19], [23, 541]], 
* Val   accuracy / confusion: 68.47% / [[131, 99], [87, 273]]

------------------------------ Epoch 370 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.060398
- Iter 028 / 029, Loss: 0.046534

* Train accuracy / confusion: 96.01% / [[348, 16], [21, 543]], 
* Val   accuracy / confusion: 68.47% / [[138, 92], [94, 266]]

------------------------------ Epoch 371 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.084089
- Iter 028 / 029, Loss: 0.050690

* Train accuracy / confusion: 95.80% / [[341, 23], [16, 548]], 
* Val   accuracy / confusion: 69.15% / [[138, 92], [90, 270]]

------------------------------ Epoch 372 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.035847
- Iter 028 / 029, Loss: 0.138778

* Train accuracy / confusion: 95.26% / [[339, 23], [21, 545]], 
* Val   accuracy / confusion: 68.14% / [[134, 96], [92, 268]]

------------------------------ Epoch 373 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.164676
- Iter 028 / 029, Loss: 0.115134

* Train accuracy / confusion: 95.58% / [[339, 21], [20, 548]], 
* Val   accuracy / confusion: 68.81% / [[126, 104], [80, 280]]

------------------------------ Epoch 374 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.130024
- Iter 028 / 029, Loss: 0.098265

* Train accuracy / confusion: 95.91% / [[347, 18], [20, 543]], 
* Val   accuracy / confusion: 72.20% / [[144, 86], [78, 282]]

------------------------------ Epoch 375 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.097255
- Iter 028 / 029, Loss: 0.142064

* Train accuracy / confusion: 95.15% / [[339, 22], [23, 544]], 
* Val   accuracy / confusion: 68.47% / [[122, 108], [78, 282]]

------------------------------ Epoch 376 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.091294
- Iter 028 / 029, Loss: 0.123829

* Train accuracy / confusion: 94.83% / [[342, 20], [28, 538]], 
* Val   accuracy / confusion: 69.15% / [[137, 93], [89, 271]]

------------------------------ Epoch 377 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.095090
- Iter 028 / 029, Loss: 0.391271

* Train accuracy / confusion: 96.23% / [[343, 17], [18, 550]], 
* Val   accuracy / confusion: 68.14% / [[125, 105], [83, 277]]

------------------------------ Epoch 378 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.068102
- Iter 028 / 029, Loss: 0.046803

* Train accuracy / confusion: 95.91% / [[337, 22], [16, 553]], 
* Val   accuracy / confusion: 70.00% / [[129, 101], [76, 284]]

------------------------------ Epoch 379 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.097318
- Iter 028 / 029, Loss: 0.089158

* Train accuracy / confusion: 96.01% / [[341, 19], [18, 550]], 
* Val   accuracy / confusion: 68.14% / [[127, 103], [85, 275]]

------------------------------ Epoch 380 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.134736
- Iter 028 / 029, Loss: 0.135595

* Train accuracy / confusion: 95.58% / [[348, 14], [27, 539]], 
* Val   accuracy / confusion: 68.47% / [[135, 95], [91, 269]]

------------------------------ Epoch 381 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.215593
- Iter 028 / 029, Loss: 0.076880

* Train accuracy / confusion: 94.72% / [[344, 18], [31, 535]], 
* Val   accuracy / confusion: 70.51% / [[139, 91], [83, 277]]

------------------------------ Epoch 382 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.111896
- Iter 028 / 029, Loss: 0.128103

* Train accuracy / confusion: 95.80% / [[342, 19], [20, 547]], 
* Val   accuracy / confusion: 67.29% / [[130, 100], [93, 267]]

------------------------------ Epoch 383 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.296732
- Iter 028 / 029, Loss: 0.267793

* Train accuracy / confusion: 95.47% / [[342, 20], [22, 544]], 
* Val   accuracy / confusion: 69.32% / [[150, 80], [101, 259]]

------------------------------ Epoch 384 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.147108
- Iter 028 / 029, Loss: 0.125893

* Train accuracy / confusion: 95.04% / [[340, 19], [27, 542]], 
* Val   accuracy / confusion: 69.49% / [[128, 102], [78, 282]]

------------------------------ Epoch 385 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.149432
- Iter 028 / 029, Loss: 0.207769

* Train accuracy / confusion: 94.61% / [[339, 19], [31, 539]], 
* Val   accuracy / confusion: 69.32% / [[141, 89], [92, 268]]

------------------------------ Epoch 386 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.190896
- Iter 028 / 029, Loss: 0.176521

* Train accuracy / confusion: 94.72% / [[335, 27], [22, 544]], 
* Val   accuracy / confusion: 68.98% / [[136, 94], [89, 271]]

------------------------------ Epoch 387 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.038842
- Iter 028 / 029, Loss: 0.096183

* Train accuracy / confusion: 95.26% / [[344, 18], [26, 540]], 
* Val   accuracy / confusion: 69.32% / [[134, 96], [85, 275]]

------------------------------ Epoch 388 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.151997
- Iter 028 / 029, Loss: 0.158945

* Train accuracy / confusion: 95.80% / [[342, 19], [20, 547]], 
* Val   accuracy / confusion: 68.47% / [[136, 94], [92, 268]]

------------------------------ Epoch 389 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.054244
- Iter 028 / 029, Loss: 0.110984

* Train accuracy / confusion: 95.47% / [[345, 20], [22, 541]], 
* Val   accuracy / confusion: 66.95% / [[130, 100], [95, 265]]

------------------------------ Epoch 390 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.063842
- Iter 028 / 029, Loss: 0.089608

* Train accuracy / confusion: 95.15% / [[337, 23], [22, 546]], 
* Val   accuracy / confusion: 66.95% / [[130, 100], [95, 265]]

------------------------------ Epoch 391 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.074373
- Iter 028 / 029, Loss: 0.108102

* Train accuracy / confusion: 96.01% / [[345, 15], [22, 546]], 
* Val   accuracy / confusion: 69.32% / [[150, 80], [101, 259]]

------------------------------ Epoch 392 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.077245
- Iter 028 / 029, Loss: 0.108548

* Train accuracy / confusion: 96.34% / [[347, 15], [19, 547]], 
* Val   accuracy / confusion: 68.14% / [[132, 98], [90, 270]]

------------------------------ Epoch 393 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.124858
- Iter 028 / 029, Loss: 0.194335

* Train accuracy / confusion: 95.80% / [[341, 22], [17, 548]], 
* Val   accuracy / confusion: 67.12% / [[134, 96], [98, 262]]

------------------------------ Epoch 394 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.135216
- Iter 028 / 029, Loss: 0.094540

* Train accuracy / confusion: 95.04% / [[339, 25], [21, 543]], 
* Val   accuracy / confusion: 68.98% / [[135, 95], [88, 272]]

------------------------------ Epoch 395 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.121714
- Iter 028 / 029, Loss: 0.167349

* Train accuracy / confusion: 93.97% / [[334, 27], [29, 538]], 
* Val   accuracy / confusion: 70.68% / [[156, 74], [99, 261]]

------------------------------ Epoch 396 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.087944
- Iter 028 / 029, Loss: 0.062862

* Train accuracy / confusion: 95.15% / [[341, 23], [22, 542]], 
* Val   accuracy / confusion: 68.81% / [[123, 107], [77, 283]]

------------------------------ Epoch 397 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.117390
- Iter 028 / 029, Loss: 0.278798

* Train accuracy / confusion: 95.15% / [[342, 23], [22, 541]], 
* Val   accuracy / confusion: 67.97% / [[135, 95], [94, 266]]

------------------------------ Epoch 398 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.060216
- Iter 028 / 029, Loss: 0.126694

* Train accuracy / confusion: 95.47% / [[342, 17], [25, 544]], 
* Val   accuracy / confusion: 68.81% / [[130, 100], [84, 276]]

------------------------------ Epoch 399 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.045156
- Iter 028 / 029, Loss: 0.279046

* Train accuracy / confusion: 95.80% / [[346, 15], [24, 543]], 
* Val   accuracy / confusion: 67.97% / [[135, 95], [94, 266]]

------------------------------ Epoch 400 / 500, Learning rate: 1.49e-05 ------------------------------
- Iter 014 / 029, Loss: 0.132515
- Iter 028 / 029, Loss: 0.138269

* Train accuracy / confusion: 95.91% / [[342, 18], [20, 548]], 
* Val   accuracy / confusion: 68.98% / [[143, 87], [96, 264]]

------------------------------ Epoch 401 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.237513
- Iter 028 / 029, Loss: 0.055975

* Train accuracy / confusion: 95.69% / [[347, 15], [25, 541]], 
* Val   accuracy / confusion: 68.47% / [[141, 89], [97, 263]]

------------------------------ Epoch 402 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.083412
- Iter 028 / 029, Loss: 0.301790

* Train accuracy / confusion: 95.37% / [[340, 21], [22, 545]], 
* Val   accuracy / confusion: 65.76% / [[130, 100], [102, 258]]

------------------------------ Epoch 403 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.096354
- Iter 028 / 029, Loss: 0.121829

* Train accuracy / confusion: 95.80% / [[342, 18], [21, 547]], 
* Val   accuracy / confusion: 67.63% / [[127, 103], [88, 272]]

------------------------------ Epoch 404 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.131755
- Iter 028 / 029, Loss: 0.079270

* Train accuracy / confusion: 95.47% / [[341, 21], [21, 545]], 
* Val   accuracy / confusion: 68.31% / [[140, 90], [97, 263]]

------------------------------ Epoch 405 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.536256
- Iter 028 / 029, Loss: 0.075495

* Train accuracy / confusion: 95.26% / [[337, 23], [21, 547]], 
* Val   accuracy / confusion: 69.15% / [[135, 95], [87, 273]]

------------------------------ Epoch 406 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.033668
- Iter 028 / 029, Loss: 0.113685

* Train accuracy / confusion: 95.58% / [[349, 14], [27, 538]], 
* Val   accuracy / confusion: 70.34% / [[148, 82], [93, 267]]

------------------------------ Epoch 407 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.227985
- Iter 028 / 029, Loss: 0.104173

* Train accuracy / confusion: 95.58% / [[343, 21], [20, 544]], 
* Val   accuracy / confusion: 70.00% / [[139, 91], [86, 274]]

------------------------------ Epoch 408 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.124025
- Iter 028 / 029, Loss: 0.102646

* Train accuracy / confusion: 95.69% / [[341, 20], [20, 547]], 
* Val   accuracy / confusion: 69.83% / [[137, 93], [85, 275]]

------------------------------ Epoch 409 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.185316
- Iter 028 / 029, Loss: 0.047892

* Train accuracy / confusion: 94.94% / [[340, 20], [27, 541]], 
* Val   accuracy / confusion: 66.61% / [[132, 98], [99, 261]]

------------------------------ Epoch 410 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.023774
- Iter 028 / 029, Loss: 0.135025

* Train accuracy / confusion: 96.01% / [[346, 17], [20, 545]], 
* Val   accuracy / confusion: 68.14% / [[137, 93], [95, 265]]

------------------------------ Epoch 411 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.200634
- Iter 028 / 029, Loss: 0.122579

* Train accuracy / confusion: 96.23% / [[345, 19], [16, 548]], 
* Val   accuracy / confusion: 68.81% / [[135, 95], [89, 271]]

------------------------------ Epoch 412 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.168961
- Iter 028 / 029, Loss: 0.082464

* Train accuracy / confusion: 95.80% / [[350, 15], [24, 539]], 
* Val   accuracy / confusion: 67.29% / [[124, 106], [87, 273]]

------------------------------ Epoch 413 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.114673
- Iter 028 / 029, Loss: 0.145782

* Train accuracy / confusion: 95.15% / [[340, 21], [24, 543]], 
* Val   accuracy / confusion: 68.31% / [[138, 92], [95, 265]]

------------------------------ Epoch 414 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.075066
- Iter 028 / 029, Loss: 0.182735

* Train accuracy / confusion: 96.44% / [[344, 18], [15, 551]], 
* Val   accuracy / confusion: 65.42% / [[120, 110], [94, 266]]

------------------------------ Epoch 415 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.043609
- Iter 028 / 029, Loss: 0.131782

* Train accuracy / confusion: 95.69% / [[343, 19], [21, 545]], 
* Val   accuracy / confusion: 69.66% / [[145, 85], [94, 266]]

------------------------------ Epoch 416 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.226917
- Iter 028 / 029, Loss: 0.149855

* Train accuracy / confusion: 96.23% / [[345, 16], [19, 548]], 
* Val   accuracy / confusion: 71.02% / [[146, 84], [87, 273]]

------------------------------ Epoch 417 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.096994
- Iter 028 / 029, Loss: 0.076587

* Train accuracy / confusion: 96.12% / [[350, 14], [22, 542]], 
* Val   accuracy / confusion: 69.15% / [[129, 101], [81, 279]]

------------------------------ Epoch 418 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.121044
- Iter 028 / 029, Loss: 0.077279

* Train accuracy / confusion: 97.09% / [[348, 12], [15, 553]], 
* Val   accuracy / confusion: 68.14% / [[134, 96], [92, 268]]

------------------------------ Epoch 419 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.229824
- Iter 028 / 029, Loss: 0.035667

* Train accuracy / confusion: 95.58% / [[343, 19], [22, 544]], 
* Val   accuracy / confusion: 68.64% / [[137, 93], [92, 268]]

------------------------------ Epoch 420 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.135769
- Iter 028 / 029, Loss: 0.036767

* Train accuracy / confusion: 96.01% / [[346, 19], [18, 545]], 
* Val   accuracy / confusion: 67.97% / [[127, 103], [86, 274]]

------------------------------ Epoch 421 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.106702
- Iter 028 / 029, Loss: 0.067549

* Train accuracy / confusion: 96.77% / [[348, 16], [14, 550]], 
* Val   accuracy / confusion: 68.64% / [[132, 98], [87, 273]]

------------------------------ Epoch 422 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.077343
- Iter 028 / 029, Loss: 0.049381

* Train accuracy / confusion: 96.23% / [[346, 18], [17, 547]], 
* Val   accuracy / confusion: 69.66% / [[136, 94], [85, 275]]

------------------------------ Epoch 423 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.078177
- Iter 028 / 029, Loss: 0.047584

* Train accuracy / confusion: 95.80% / [[345, 18], [21, 544]], 
* Val   accuracy / confusion: 69.49% / [[140, 90], [90, 270]]

------------------------------ Epoch 424 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.108157
- Iter 028 / 029, Loss: 0.058163

* Train accuracy / confusion: 96.88% / [[353, 11], [18, 546]], 
* Val   accuracy / confusion: 68.47% / [[135, 95], [91, 269]]

------------------------------ Epoch 425 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.069349
- Iter 028 / 029, Loss: 0.142515

* Train accuracy / confusion: 96.12% / [[345, 18], [18, 547]], 
* Val   accuracy / confusion: 69.15% / [[140, 90], [92, 268]]

------------------------------ Epoch 426 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.088471
- Iter 028 / 029, Loss: 0.135875

* Train accuracy / confusion: 96.66% / [[346, 14], [17, 551]], 
* Val   accuracy / confusion: 68.64% / [[138, 92], [93, 267]]

------------------------------ Epoch 427 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.076951
- Iter 028 / 029, Loss: 0.150752

* Train accuracy / confusion: 95.91% / [[340, 21], [17, 550]], 
* Val   accuracy / confusion: 69.49% / [[138, 92], [88, 272]]

------------------------------ Epoch 428 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.079060
- Iter 028 / 029, Loss: 0.050776

* Train accuracy / confusion: 95.80% / [[346, 17], [22, 543]], 
* Val   accuracy / confusion: 67.12% / [[130, 100], [94, 266]]

------------------------------ Epoch 429 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.114599
- Iter 028 / 029, Loss: 0.041878

* Train accuracy / confusion: 96.12% / [[349, 17], [19, 543]], 
* Val   accuracy / confusion: 67.97% / [[132, 98], [91, 269]]

------------------------------ Epoch 430 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.057967
- Iter 028 / 029, Loss: 0.086929

* Train accuracy / confusion: 96.44% / [[351, 14], [19, 544]], 
* Val   accuracy / confusion: 67.80% / [[130, 100], [90, 270]]

------------------------------ Epoch 431 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.125219
- Iter 028 / 029, Loss: 0.105233

* Train accuracy / confusion: 95.26% / [[346, 19], [25, 538]], 
* Val   accuracy / confusion: 68.64% / [[138, 92], [93, 267]]

------------------------------ Epoch 432 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.065211
- Iter 028 / 029, Loss: 0.255204

* Train accuracy / confusion: 95.91% / [[349, 13], [25, 541]], 
* Val   accuracy / confusion: 66.10% / [[122, 108], [92, 268]]

------------------------------ Epoch 433 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.135067
- Iter 028 / 029, Loss: 0.121208

* Train accuracy / confusion: 94.94% / [[342, 23], [24, 539]], 
* Val   accuracy / confusion: 68.81% / [[130, 100], [84, 276]]

------------------------------ Epoch 434 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.028629
- Iter 028 / 029, Loss: 0.076290

* Train accuracy / confusion: 96.23% / [[347, 17], [18, 546]], 
* Val   accuracy / confusion: 69.66% / [[135, 95], [84, 276]]

------------------------------ Epoch 435 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.046568
- Iter 028 / 029, Loss: 0.189631

* Train accuracy / confusion: 95.58% / [[347, 16], [25, 540]], 
* Val   accuracy / confusion: 67.12% / [[122, 108], [86, 274]]

------------------------------ Epoch 436 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.158209
- Iter 028 / 029, Loss: 0.047177

* Train accuracy / confusion: 97.52% / [[350, 12], [11, 555]], 
* Val   accuracy / confusion: 67.63% / [[128, 102], [89, 271]]

------------------------------ Epoch 437 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.281356
- Iter 028 / 029, Loss: 0.094443

* Train accuracy / confusion: 96.23% / [[348, 16], [19, 545]], 
* Val   accuracy / confusion: 69.83% / [[134, 96], [82, 278]]

------------------------------ Epoch 438 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.048986
- Iter 028 / 029, Loss: 0.086678

* Train accuracy / confusion: 95.91% / [[336, 21], [17, 554]], 
* Val   accuracy / confusion: 66.95% / [[133, 97], [98, 262]]

------------------------------ Epoch 439 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.053258
- Iter 028 / 029, Loss: 0.031636

* Train accuracy / confusion: 97.31% / [[348, 11], [14, 555]], 
* Val   accuracy / confusion: 67.80% / [[133, 97], [93, 267]]

------------------------------ Epoch 440 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.161576
- Iter 028 / 029, Loss: 0.107981

* Train accuracy / confusion: 95.69% / [[343, 18], [22, 545]], 
* Val   accuracy / confusion: 68.47% / [[132, 98], [88, 272]]

------------------------------ Epoch 441 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.072994
- Iter 028 / 029, Loss: 0.182703

* Train accuracy / confusion: 96.01% / [[341, 23], [14, 550]], 
* Val   accuracy / confusion: 70.17% / [[143, 87], [89, 271]]

------------------------------ Epoch 442 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.106194
- Iter 028 / 029, Loss: 0.050003

* Train accuracy / confusion: 97.52% / [[353, 11], [12, 552]], 
* Val   accuracy / confusion: 67.63% / [[132, 98], [93, 267]]

------------------------------ Epoch 443 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.030229
- Iter 028 / 029, Loss: 0.141357

* Train accuracy / confusion: 95.47% / [[339, 22], [20, 547]], 
* Val   accuracy / confusion: 69.66% / [[130, 100], [79, 281]]

------------------------------ Epoch 444 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.132710
- Iter 028 / 029, Loss: 0.093640

* Train accuracy / confusion: 95.58% / [[346, 18], [23, 541]], 
* Val   accuracy / confusion: 69.15% / [[140, 90], [92, 268]]

------------------------------ Epoch 445 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.218216
- Iter 028 / 029, Loss: 0.135777

* Train accuracy / confusion: 95.47% / [[343, 19], [23, 543]], 
* Val   accuracy / confusion: 67.46% / [[142, 88], [104, 256]]

------------------------------ Epoch 446 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.086350
- Iter 028 / 029, Loss: 0.146090

* Train accuracy / confusion: 96.55% / [[345, 22], [10, 551]], 
* Val   accuracy / confusion: 68.64% / [[134, 96], [89, 271]]

------------------------------ Epoch 447 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.134305
- Iter 028 / 029, Loss: 0.064454

* Train accuracy / confusion: 96.01% / [[346, 17], [20, 545]], 
* Val   accuracy / confusion: 66.95% / [[140, 90], [105, 255]]

------------------------------ Epoch 448 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.053172
- Iter 028 / 029, Loss: 0.122888

* Train accuracy / confusion: 96.34% / [[348, 16], [18, 546]], 
* Val   accuracy / confusion: 70.51% / [[132, 98], [76, 284]]

------------------------------ Epoch 449 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.054928
- Iter 028 / 029, Loss: 0.076952

* Train accuracy / confusion: 96.66% / [[348, 15], [16, 549]], 
* Val   accuracy / confusion: 68.31% / [[132, 98], [89, 271]]

------------------------------ Epoch 450 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.115848
- Iter 028 / 029, Loss: 0.039075

* Train accuracy / confusion: 95.58% / [[346, 18], [23, 541]], 
* Val   accuracy / confusion: 69.49% / [[141, 89], [91, 269]]

------------------------------ Epoch 451 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.051524
- Iter 028 / 029, Loss: 0.067687

* Train accuracy / confusion: 96.55% / [[342, 18], [14, 554]], 
* Val   accuracy / confusion: 66.78% / [[125, 105], [91, 269]]

------------------------------ Epoch 452 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.115501
- Iter 028 / 029, Loss: 0.050829

* Train accuracy / confusion: 96.12% / [[347, 17], [19, 545]], 
* Val   accuracy / confusion: 65.59% / [[125, 105], [98, 262]]

------------------------------ Epoch 453 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.047655
- Iter 028 / 029, Loss: 0.079629

* Train accuracy / confusion: 93.32% / [[333, 28], [34, 533]], 
* Val   accuracy / confusion: 68.14% / [[133, 97], [91, 269]]

------------------------------ Epoch 454 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.174648
- Iter 028 / 029, Loss: 0.158397

* Train accuracy / confusion: 95.26% / [[343, 22], [22, 541]], 
* Val   accuracy / confusion: 66.78% / [[132, 98], [98, 262]]

------------------------------ Epoch 455 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.030240
- Iter 028 / 029, Loss: 0.227123

* Train accuracy / confusion: 96.34% / [[341, 18], [16, 553]], 
* Val   accuracy / confusion: 67.97% / [[138, 92], [97, 263]]

------------------------------ Epoch 456 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.073953
- Iter 028 / 029, Loss: 0.128817

* Train accuracy / confusion: 96.12% / [[347, 16], [20, 545]], 
* Val   accuracy / confusion: 68.64% / [[129, 101], [84, 276]]

------------------------------ Epoch 457 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.146884
- Iter 028 / 029, Loss: 0.063756

* Train accuracy / confusion: 95.47% / [[350, 12], [30, 536]], 
* Val   accuracy / confusion: 68.64% / [[133, 97], [88, 272]]

------------------------------ Epoch 458 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.178239
- Iter 028 / 029, Loss: 0.234102

* Train accuracy / confusion: 95.91% / [[341, 17], [21, 549]], 
* Val   accuracy / confusion: 67.80% / [[139, 91], [99, 261]]

------------------------------ Epoch 459 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.034874
- Iter 028 / 029, Loss: 0.179232

* Train accuracy / confusion: 96.77% / [[343, 17], [13, 555]], 
* Val   accuracy / confusion: 71.19% / [[138, 92], [78, 282]]

------------------------------ Epoch 460 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.139736
- Iter 028 / 029, Loss: 0.029849

* Train accuracy / confusion: 95.80% / [[345, 19], [20, 544]], 
* Val   accuracy / confusion: 67.12% / [[126, 104], [90, 270]]

------------------------------ Epoch 461 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.184993
- Iter 028 / 029, Loss: 0.046089

* Train accuracy / confusion: 95.37% / [[341, 23], [20, 544]], 
* Val   accuracy / confusion: 69.49% / [[126, 104], [76, 284]]

------------------------------ Epoch 462 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.091869
- Iter 028 / 029, Loss: 0.136981

* Train accuracy / confusion: 95.47% / [[341, 22], [20, 545]], 
* Val   accuracy / confusion: 69.15% / [[137, 93], [89, 271]]

------------------------------ Epoch 463 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.128592
- Iter 028 / 029, Loss: 0.180212

* Train accuracy / confusion: 96.88% / [[351, 12], [17, 548]], 
* Val   accuracy / confusion: 69.49% / [[133, 97], [83, 277]]

------------------------------ Epoch 464 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.088563
- Iter 028 / 029, Loss: 0.133423

* Train accuracy / confusion: 96.12% / [[345, 17], [19, 547]], 
* Val   accuracy / confusion: 69.49% / [[132, 98], [82, 278]]

------------------------------ Epoch 465 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.227797
- Iter 028 / 029, Loss: 0.193109

* Train accuracy / confusion: 95.69% / [[341, 22], [18, 547]], 
* Val   accuracy / confusion: 70.34% / [[137, 93], [82, 278]]

------------------------------ Epoch 466 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.038736
- Iter 028 / 029, Loss: 0.035798

* Train accuracy / confusion: 96.01% / [[345, 17], [20, 546]], 
* Val   accuracy / confusion: 68.81% / [[136, 94], [90, 270]]

------------------------------ Epoch 467 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.027401
- Iter 028 / 029, Loss: 0.173052

* Train accuracy / confusion: 95.37% / [[348, 17], [26, 537]], 
* Val   accuracy / confusion: 70.00% / [[141, 89], [88, 272]]

------------------------------ Epoch 468 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.070569
- Iter 028 / 029, Loss: 0.293686

* Train accuracy / confusion: 95.26% / [[338, 23], [21, 546]], 
* Val   accuracy / confusion: 67.29% / [[133, 97], [96, 264]]

------------------------------ Epoch 469 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.132061
- Iter 028 / 029, Loss: 0.171037

* Train accuracy / confusion: 96.44% / [[343, 16], [17, 552]], 
* Val   accuracy / confusion: 68.14% / [[135, 95], [93, 267]]

------------------------------ Epoch 470 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.151103
- Iter 028 / 029, Loss: 0.260848

* Train accuracy / confusion: 96.12% / [[346, 16], [20, 546]], 
* Val   accuracy / confusion: 67.29% / [[130, 100], [93, 267]]

------------------------------ Epoch 471 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.102812
- Iter 028 / 029, Loss: 0.051766

* Train accuracy / confusion: 95.80% / [[343, 18], [21, 546]], 
* Val   accuracy / confusion: 67.29% / [[139, 91], [102, 258]]

------------------------------ Epoch 472 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.128959
- Iter 028 / 029, Loss: 0.093581

* Train accuracy / confusion: 96.01% / [[343, 18], [19, 548]], 
* Val   accuracy / confusion: 70.17% / [[146, 84], [92, 268]]

------------------------------ Epoch 473 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.027948
- Iter 028 / 029, Loss: 0.062456

* Train accuracy / confusion: 96.12% / [[344, 18], [18, 548]], 
* Val   accuracy / confusion: 70.17% / [[141, 89], [87, 273]]

------------------------------ Epoch 474 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.079242
- Iter 028 / 029, Loss: 0.039042

* Train accuracy / confusion: 95.80% / [[345, 17], [22, 544]], 
* Val   accuracy / confusion: 68.14% / [[139, 91], [97, 263]]

------------------------------ Epoch 475 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.025607
- Iter 028 / 029, Loss: 0.044385

* Train accuracy / confusion: 97.31% / [[349, 13], [12, 554]], 
* Val   accuracy / confusion: 69.15% / [[134, 96], [86, 274]]

------------------------------ Epoch 476 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.084146
- Iter 028 / 029, Loss: 0.068546

* Train accuracy / confusion: 95.58% / [[341, 21], [20, 546]], 
* Val   accuracy / confusion: 67.80% / [[132, 98], [92, 268]]

------------------------------ Epoch 477 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.040945
- Iter 028 / 029, Loss: 0.099209

* Train accuracy / confusion: 96.34% / [[348, 16], [18, 546]], 
* Val   accuracy / confusion: 67.97% / [[133, 97], [92, 268]]

------------------------------ Epoch 478 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.072418
- Iter 028 / 029, Loss: 0.107717

* Train accuracy / confusion: 95.80% / [[345, 18], [21, 544]], 
* Val   accuracy / confusion: 70.00% / [[133, 97], [80, 280]]

------------------------------ Epoch 479 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.150617
- Iter 028 / 029, Loss: 0.079746

* Train accuracy / confusion: 95.37% / [[341, 20], [23, 544]], 
* Val   accuracy / confusion: 68.64% / [[133, 97], [88, 272]]

------------------------------ Epoch 480 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.186572
- Iter 028 / 029, Loss: 0.119531

* Train accuracy / confusion: 95.15% / [[341, 23], [22, 542]], 
* Val   accuracy / confusion: 67.80% / [[123, 107], [83, 277]]

------------------------------ Epoch 481 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.051727
- Iter 028 / 029, Loss: 0.077782

* Train accuracy / confusion: 95.91% / [[348, 17], [21, 542]], 
* Val   accuracy / confusion: 68.31% / [[131, 99], [88, 272]]

------------------------------ Epoch 482 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.058730
- Iter 028 / 029, Loss: 0.098556

* Train accuracy / confusion: 96.01% / [[347, 17], [20, 544]], 
* Val   accuracy / confusion: 67.97% / [[140, 90], [99, 261]]

------------------------------ Epoch 483 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.209312
- Iter 028 / 029, Loss: 0.054987

* Train accuracy / confusion: 95.58% / [[342, 20], [21, 545]], 
* Val   accuracy / confusion: 68.14% / [[139, 91], [97, 263]]

------------------------------ Epoch 484 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.042597
- Iter 028 / 029, Loss: 0.180206

* Train accuracy / confusion: 96.01% / [[346, 18], [19, 545]], 
* Val   accuracy / confusion: 70.00% / [[135, 95], [82, 278]]

------------------------------ Epoch 485 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.134356
- Iter 028 / 029, Loss: 0.029426

* Train accuracy / confusion: 95.58% / [[343, 21], [20, 544]], 
* Val   accuracy / confusion: 68.31% / [[138, 92], [95, 265]]

------------------------------ Epoch 486 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.125447
- Iter 028 / 029, Loss: 0.030007

* Train accuracy / confusion: 95.80% / [[343, 21], [18, 546]], 
* Val   accuracy / confusion: 68.31% / [[137, 93], [94, 266]]

------------------------------ Epoch 487 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.154751
- Iter 028 / 029, Loss: 0.130918

* Train accuracy / confusion: 96.23% / [[346, 16], [19, 547]], 
* Val   accuracy / confusion: 67.63% / [[132, 98], [93, 267]]

------------------------------ Epoch 488 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.366435
- Iter 028 / 029, Loss: 0.044555

* Train accuracy / confusion: 95.91% / [[345, 19], [19, 545]], 
* Val   accuracy / confusion: 68.64% / [[132, 98], [87, 273]]

------------------------------ Epoch 489 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.026684
- Iter 028 / 029, Loss: 0.120974

* Train accuracy / confusion: 96.34% / [[343, 19], [15, 551]], 
* Val   accuracy / confusion: 69.15% / [[140, 90], [92, 268]]

------------------------------ Epoch 490 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.086689
- Iter 028 / 029, Loss: 0.108821

* Train accuracy / confusion: 95.91% / [[343, 17], [21, 547]], 
* Val   accuracy / confusion: 69.32% / [[137, 93], [88, 272]]

------------------------------ Epoch 491 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.098474
- Iter 028 / 029, Loss: 0.075248

* Train accuracy / confusion: 96.12% / [[342, 17], [19, 550]], 
* Val   accuracy / confusion: 67.46% / [[138, 92], [100, 260]]

------------------------------ Epoch 492 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.150741
- Iter 028 / 029, Loss: 0.028571

* Train accuracy / confusion: 95.58% / [[342, 21], [20, 545]], 
* Val   accuracy / confusion: 67.46% / [[136, 94], [98, 262]]

------------------------------ Epoch 493 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.051815
- Iter 028 / 029, Loss: 0.098035

* Train accuracy / confusion: 96.01% / [[345, 19], [18, 546]], 
* Val   accuracy / confusion: 67.63% / [[133, 97], [94, 266]]

------------------------------ Epoch 494 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.100851
- Iter 028 / 029, Loss: 0.057548

* Train accuracy / confusion: 95.80% / [[343, 19], [20, 546]], 
* Val   accuracy / confusion: 67.29% / [[129, 101], [92, 268]]

------------------------------ Epoch 495 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.049827
- Iter 028 / 029, Loss: 0.069832

* Train accuracy / confusion: 96.66% / [[348, 14], [17, 549]], 
* Val   accuracy / confusion: 69.32% / [[141, 89], [92, 268]]

------------------------------ Epoch 496 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.264310
- Iter 028 / 029, Loss: 0.116756

* Train accuracy / confusion: 95.47% / [[345, 19], [23, 541]], 
* Val   accuracy / confusion: 68.47% / [[128, 102], [84, 276]]

------------------------------ Epoch 497 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.161066
- Iter 028 / 029, Loss: 0.034416

* Train accuracy / confusion: 96.66% / [[345, 15], [16, 552]], 
* Val   accuracy / confusion: 65.93% / [[126, 104], [97, 263]]

------------------------------ Epoch 498 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.164108
- Iter 028 / 029, Loss: 0.346033

* Train accuracy / confusion: 95.26% / [[340, 21], [23, 544]], 
* Val   accuracy / confusion: 70.34% / [[141, 89], [86, 274]]

------------------------------ Epoch 499 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.057385
- Iter 028 / 029, Loss: 0.142656

* Train accuracy / confusion: 95.80% / [[339, 18], [21, 550]], 
* Val   accuracy / confusion: 65.59% / [[127, 103], [100, 260]]

------------------------------ Epoch 500 / 500, Learning rate: 1.49e-06 ------------------------------
- Iter 014 / 029, Loss: 0.063247
- Iter 028 / 029, Loss: 0.294175

* Train accuracy / confusion: 96.77% / [[348, 15], [15, 550]], 
* Val   accuracy / confusion: 66.61% / [[127, 103], [94, 266]]

**************************************** Training Ends ****************************************

- Test accuracy (last model): 69.11%
- Confusion matrix (last model):
 [[ 961  449]
 [ 663 1527]]

- Test accuracy (best model): 73.25%
- Confusion matrix (best model):
 [[ 867  543]
 [ 420 1770]]

# checkpoint save path
if save_checkpoint:
    os.makedirs('checkpoint/', exist_ok=True)
    today = datetime.date.today()
    torch.save(best_model_state, f'checkpoint/{today.year % 100}{today.month:02d}{today.day}_{nb_fname}_TinyResNet_best')
    torch.save(last_model_state, f'checkpoint/{today.year % 100}{today.month:02d}{today.day}_{nb_fname}_TinyResNet_last')

print('- Debug table:')
pprint.pp(last_test_debug, indent=2, width=100)

- Debug table:
{ '01183': {'GT': 1, 'Acc': ' 53.33%', 'Pred': [14, 16], 'edfname': '01303198_020317'},
  '00697': {'GT': 0, 'Acc': '  0.00%', 'Pred': [0, 30], 'edfname': '00983533_290618'},
  '00825': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01129445_130220'},
  '00504': {'GT': 0, 'Acc': '  6.67%', 'Pred': [2, 28], 'edfname': '00813343_041218'},
  '00192': {'GT': 0, 'Acc': ' 80.00%', 'Pred': [24, 6], 'edfname': '00608961_131118'},
  '00134': {'GT': 1, 'Acc': ' 70.00%', 'Pred': [9, 21], 'edfname': '00446328_171116'},
  '00741': {'GT': 0, 'Acc': ' 53.33%', 'Pred': [16, 14], 'edfname': '01025734_280715'},
  '00206': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00616193_090218'},
  '01231': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01334787_211117'},
  '00793': {'GT': 0, 'Acc': ' 93.33%', 'Pred': [28, 2], 'edfname': '01086373_020615'},
  '01045': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01235281_191015'},
  '00407': {'GT': 1, 'Acc': ' 53.33%', 'Pred': [14, 16], 'edfname': '00740694_110315'},
  '00669': {'GT': 1, 'Acc': ' 23.33%', 'Pred': [23, 7], 'edfname': '00957862_230317'},
  '00843': {'GT': 1, 'Acc': '  0.00%', 'Pred': [30, 0], 'edfname': '01135545_230715'},
  '00029': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00164098_180919'},
  '00299': {'GT': 0, 'Acc': ' 70.00%', 'Pred': [21, 9], 'edfname': '00671212_160819'},
  '00702': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '00985987_180518'},
  '01069': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01243158_301115'},
  '00913': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01151967_160414'},
  '01307': {'GT': 0, 'Acc': '  6.67%', 'Pred': [2, 28], 'edfname': '01376302_060718'},
  '00638': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00941649_111218'},
  '00286': {'GT': 1, 'Acc': '  0.00%', 'Pred': [30, 0], 'edfname': '00663561_030414'},
  '00954': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '01178797_240914'},
  '00587': {'GT': 1, 'Acc': ' 70.00%', 'Pred': [9, 21], 'edfname': '00894185_250817'},
  '00542': {'GT': 1, 'Acc': ' 20.00%', 'Pred': [24, 6], 'edfname': '00852650_170818'},
  '00996': {'GT': 1, 'Acc': ' 46.67%', 'Pred': [16, 14], 'edfname': '01204692_120315'},
  '00403': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00739162_011215'},
  '00408': {'GT': 0, 'Acc': ' 50.00%', 'Pred': [15, 15], 'edfname': '00740750_110315'},
  '00078': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00324958_271118'},
  '00277': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '00657017_281218'},
  '00671': {'GT': 0, 'Acc': ' 93.33%', 'Pred': [28, 2], 'edfname': '00958455_200917'},
  '01066': {'GT': 0, 'Acc': ' 46.67%', 'Pred': [14, 16], 'edfname': '01242983_071215'},
  '00965': {'GT': 1, 'Acc': '  0.00%', 'Pred': [30, 0], 'edfname': '01186214'},
  '01125': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01276737_300616'},
  '00227': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00626957_071217'},
  '00531': {'GT': 0, 'Acc': ' 93.33%', 'Pred': [28, 2], 'edfname': '00840844_250119'},
  '00088': {'GT': 1, 'Acc': ' 33.33%', 'Pred': [20, 10], 'edfname': '00344923_021116'},
  '00267': {'GT': 1, 'Acc': ' 73.33%', 'Pred': [8, 22], 'edfname': '00650465_160318'},
  '00069': {'GT': 1, 'Acc': ' 60.00%', 'Pred': [12, 18], 'edfname': '00307906_230617'},
  '00365': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00712852_060418'},
  '00991': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01203444_090819'},
  '00815': {'GT': 0, 'Acc': ' 66.67%', 'Pred': [20, 10], 'edfname': '01125477_030918'},
  '01351': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01409497_111219'},
  '00065': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00293228_070918'},
  '00952': {'GT': 1, 'Acc': ' 26.67%', 'Pred': [22, 8], 'edfname': '01178672_300518'},
  '00124': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00418981_060116'},
  '00854': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01138301_230114'},
  '00472': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '00784418_201016'},
  '01258': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '01348039_181017'},
  '01375': {'GT': 1, 'Acc': ' 36.67%', 'Pred': [19, 11], 'edfname': '01429374_230519'},
  '00885': {'GT': 0, 'Acc': ' 23.33%', 'Pred': [7, 23], 'edfname': '01142810_180214'},
  '00917': {'GT': 0, 'Acc': ' 83.33%', 'Pred': [25, 5], 'edfname': '01154159_230414'},
  '00938': {'GT': 0, 'Acc': '  0.00%', 'Pred': [0, 30], 'edfname': '01161826_050916'},
  '00881': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01141790_190214'},
  '00096': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00369252_131216'},
  '01075': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01250004_260116'},
  '01165': {'GT': 0, 'Acc': '  3.33%', 'Pred': [1, 29], 'edfname': '01296533_281116'},
  '01067': {'GT': 1, 'Acc': ' 20.00%', 'Pred': [24, 6], 'edfname': '01242984_211215'},
  '00828': {'GT': 1, 'Acc': ' 56.67%', 'Pred': [13, 17], 'edfname': '01131959_310118'},
  '01337': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01400560_160419'},
  '00383': {'GT': 1, 'Acc': ' 56.67%', 'Pred': [13, 17], 'edfname': '00723110_240419'},
  '00900': {'GT': 0, 'Acc': ' 76.67%', 'Pred': [23, 7], 'edfname': '01147100'},
  '01336': {'GT': 1, 'Acc': ' 70.00%', 'Pred': [9, 21], 'edfname': '01398060_050918'},
  '01115': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01271298_270319'},
  '00667': {'GT': 1, 'Acc': ' 73.33%', 'Pred': [8, 22], 'edfname': '00956561_241116'},
  '00439': {'GT': 0, 'Acc': ' 90.00%', 'Pred': [27, 3], 'edfname': '00760780_141118'},
  '00369': {'GT': 1, 'Acc': ' 20.00%', 'Pred': [24, 6], 'edfname': '00715828_111016'},
  '00955': {'GT': 1, 'Acc': ' 40.00%', 'Pred': [18, 12], 'edfname': '01178888_161117'},
  '00300': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00671379_290617'},
  '01196': {'GT': 1, 'Acc': ' 20.00%', 'Pred': [24, 6], 'edfname': '01307883_100217'},
  '00923': {'GT': 0, 'Acc': '  3.33%', 'Pred': [1, 29], 'edfname': '01155730_070514'},
  '00058': {'GT': 0, 'Acc': ' 76.67%', 'Pred': [23, 7], 'edfname': '00285244_020414'},
  '00584': {'GT': 1, 'Acc': '  0.00%', 'Pred': [30, 0], 'edfname': '00891889_060717'},
  '00749': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01027623_260916'},
  '01334': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '01396872_021018'},
  '00588': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00895530_090616'},
  '00679': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00963069_150618'},
  '00385': {'GT': 0, 'Acc': ' 13.33%', 'Pred': [4, 26], 'edfname': '00723232_270318'},
  '00018': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00128526_180817'},
  '01281': {'GT': 1, 'Acc': ' 66.67%', 'Pred': [10, 20], 'edfname': '01358607_280918'},
  '00651': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00951808_251116'},
  '01253': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '01344212_240817'},
  '01035': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '01231654_260417'},
  '00551': {'GT': 1, 'Acc': ' 43.33%', 'Pred': [17, 13], 'edfname': '00865039_170816'},
  '00870': {'GT': 0, 'Acc': ' 23.33%', 'Pred': [7, 23], 'edfname': '01139947_120214'},
  '00578': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '00888613_080618'},
  '00730': {'GT': 0, 'Acc': ' 93.33%', 'Pred': [28, 2], 'edfname': '01011922_270815'},
  '00516': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00823206_130514'},
  '01330': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01392885_240718'},
  '00944': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01168853_070316'},
  '00125': {'GT': 0, 'Acc': ' 60.00%', 'Pred': [18, 12], 'edfname': '00418981_090316'},
  '00508': {'GT': 0, 'Acc': ' 66.67%', 'Pred': [20, 10], 'edfname': '00817022_010415'},
  '01317': {'GT': 1, 'Acc': ' 43.33%', 'Pred': [17, 13], 'edfname': '01381606_160518'},
  '00608': {'GT': 1, 'Acc': '  0.00%', 'Pred': [30, 0], 'edfname': '00907971_030217'},
  '00471': {'GT': 1, 'Acc': ' 73.33%', 'Pred': [8, 22], 'edfname': '00784417_100315'},
  '00821': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01128393_300715'},
  '00122': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00416942_190516'},
  '01007': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01211467_070415'},
  '01247': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '01339759_310717'},
  '00173': {'GT': 1, 'Acc': ' 63.33%', 'Pred': [11, 19], 'edfname': '00601028_290618'},
  '01026': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01225123_050815'},
  '01018': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01216443_240518'},
  '00418': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00745209_220916'},
  '01206': {'GT': 1, 'Acc': '  3.33%', 'Pred': [29, 1], 'edfname': '01314786_200317'},
  '01215': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01321744_130417'},
  '01105': {'GT': 0, 'Acc': ' 80.00%', 'Pred': [24, 6], 'edfname': '01266696_110516'},
  '00598': {'GT': 1, 'Acc': ' 60.00%', 'Pred': [12, 18], 'edfname': '00899964_110414'},
  '00851': {'GT': 0, 'Acc': '  6.67%', 'Pred': [2, 28], 'edfname': '01138297_230114'},
  '01138': {'GT': 0, 'Acc': ' 53.33%', 'Pred': [16, 14], 'edfname': '01281605_070716'},
  '00079': {'GT': 1, 'Acc': ' 86.67%', 'Pred': [4, 26], 'edfname': '00325929_170119'},
  '00245': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00637371_050917'},
  '00591': {'GT': 0, 'Acc': ' 83.33%', 'Pred': [25, 5], 'edfname': '00896386_240914'},
  '00329': {'GT': 0, 'Acc': ' 30.00%', 'Pred': [9, 21], 'edfname': '00685248_150414'},
  '00272': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '00651389_281016'},
  '00176': {'GT': 0, 'Acc': ' 86.67%', 'Pred': [26, 4], 'edfname': '00602435_270217'},
  '00807': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '01112291_231115'},
  '00271': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '00651252_140618'},
  '00712': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '00988278_210915'},
  '00974': {'GT': 1, 'Acc': ' 33.33%', 'Pred': [20, 10], 'edfname': '01193508_171214'},
  '01163': {'GT': 1, 'Acc': '  6.67%', 'Pred': [28, 2], 'edfname': '01296342_141116'}}

Network Visualization Test

signal_headers = ['Fp1-AVG', 'F3-AVG', 'C3-AVG', 'P3-AVG', 
          'O1-AVG', 'Fp2-AVG', 'F4-AVG', 'C4-AVG', 
          'P4-AVG', 'O2-AVG', 'F7-AVG', 'T3-AVG', 
          'T5-AVG', 'F8-AVG', 'T4-AVG', 'T6-AVG', 
          'FZ-AVG', 'CZ-AVG', 'PZ-AVG', 'EKG']

from scipy.ndimage.filters import gaussian_filter1d

def jitter(X, amount):
    left = X[:, :, :-amount]
    right = X[:, :, -amount:]
    X = torch.cat([left, right], dim=2)
    return X


def blur_signal(X, sigma=1):
    X_np = X.cpu().clone().numpy()
    X_np = gaussian_filter1d(X_np, sigma, axis=2)
    X.copy_(torch.Tensor(X_np).type_as(X))
    return X

def create_class_visualization(target_y, model, dtype, **kwargs):
    """
    Generate an image to maximize the score of target_y under a pretrained model.
    
    Inputs:
    - target_y: Integer in the range [0, 1000) giving the index of the class
    - model: A pretrained CNN that will be used to generate the image
    - dtype: Torch datatype to use for computations
    
    Keyword arguments:
    - l2_reg: Strength of L2 regularization on the image
    - learning_rate: How big of a step to take
    - num_iterations: How many iterations to use
    - blur_every: How often to blur the image as an implicit regularizer
    - max_jitter: How much to gjitter the image as an implicit regularizer
    - show_every: How often to show the intermediate result
    """
    model.type(dtype)
    
    l2_reg = kwargs.pop('l2_reg', 1e-3)
    learning_rate = kwargs.pop('learning_rate', 25)
    num_iterations = kwargs.pop('num_iterations', 15000)
    blur_every = kwargs.pop('blur_every', 10)
    max_jitter = kwargs.pop('max_jitter', 100)
    show_every = kwargs.pop('show_every', 5000)

    # Randomly initialize the image as a PyTorch Tensor, and make it requires gradient.
    signal = torch.randn(2, *train_dataset[0]['signal'].shape).mul_(1.0).type(dtype).requires_grad_().to(device)
    blur_signal(signal.data, sigma=3)
    
    for t in tqdm(range(num_iterations)):
        # Randomly jitter the image a bit; this gives slightly nicer results
        jittering = random.randint(0, max_jitter)
        signal.data.copy_(jitter(signal.data, jittering))

        # run the model
        age = torch.tensor([age_mean, age_mean], dtype=torch.float32).to(device)
        scores = model(signal, age)
        
        # score loss and L-2 regularization
        loss = scores[:, target_y] - l2_reg * torch.norm(signal)
        loss = loss.sum()
        
        # compute the gradients on the image
        loss.backward()
        with torch.no_grad():
            # gradient ascent
            signal += learning_rate * signal.grad
            # manually zero the gradients after running the backward pass
            signal.grad.zero_() 
        
        # Undo the random jitter
        signal.data.copy_(jitter(signal.data, -jittering))

        # As regularizer, periodically blur the image
        if t % blur_every == 0:
            blur_signal(signal.data, sigma=1)
        
        # Periodically show the signal
        if t == 0 or (t + 1) % show_every == 0 or t == num_iterations - 1:            
            fig = plt.figure(num=1, clear=True, 
                             figsize=(15.0, 10.0), constrained_layout=True)
            
            for s in range(signal.shape[0]):
                ax = fig.add_subplot(signal.shape[0], 1, s + 1)            
                sig = signal[s].data.clone().cpu()
            
                for (k, h) in enumerate(signal_headers):
                    ax.plot(np.arange(sig.shape[1]) / 200, sig[k], label=h)

                    class_name = class_label_to_type[target_y]
                    plt.legend(shadow=True).get_frame().set_facecolor('white')
                    plt.title('%s\nIteration %d / %d' % (class_name, t + 1, num_iterations))
            plt.show()
            fig.clear()
            plt.close(fig)

    return signal

#dtype = torch.FloatTensor
dtype = torch.cuda.FloatTensor # Uncomment this to use GPU
model.type(dtype)

target_y = 0 # Normal, NV-MCI, NV-Dementia
out = create_class_visualization(target_y, model, dtype)

age = torch.tensor([age_mean, age_mean], dtype=torch.float32).to(device)
scores = model(out, age)
pred = F.log_softmax(scores, dim=1)
estimation = pred.argmax(dim=-1)
print(scores)
print(pred)
print(estimation)

tensor([[ 482.8104, -203.5646],
        [ 484.6816, -206.3222]], device='cuda:0', grad_fn=<AddmmBackward>)
tensor([[   0.0000, -686.3750],
        [   0.0000, -691.0038]], device='cuda:0', grad_fn=<LogSoftmaxBackward>)
tensor([0, 0], device='cuda:0')